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<!DOCTYPE html>
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<h3><a href="index.html">Table of Contents</a></h3>
<ul>
<li><a class="reference internal" href="#">API Reference (0.1.2)</a><ul>
<li><a class="reference internal" href="#fat-forensics">FAT Forensics</a></li>
<li><a class="reference internal" href="#module-fatf.fairness"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness</span></code>: Fairness</a><ul>
<li><a class="reference internal" href="#module-fatf.fairness.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.data</span></code>: Fairness for Data</a></li>
<li><a class="reference internal" href="#module-fatf.fairness.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.models</span></code>: Fairness for Models</a></li>
<li><a class="reference internal" href="#module-fatf.fairness.predictions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.predictions</span></code>: Fairness for Predictions</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.accountability"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.accountability</span></code>: Accountability</a><ul>
<li><a class="reference internal" href="#module-fatf.accountability.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.accountability.data</span></code>: Accountability for Data</a></li>
<li><a class="reference internal" href="#module-fatf.accountability.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.accountability.models</span></code>: Accountability for Models</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.transparency"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency</span></code>: Transparency</a><ul>
<li><a class="reference internal" href="#module-fatf.transparency.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.data</span></code>: Transparency for Data</a></li>
<li><a class="reference internal" href="#module-fatf.transparency.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.models</span></code>: Transparency for Models</a><ul>
<li><a class="reference internal" href="#module-fatf.transparency.models.feature_influence"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.models.feature_influence</span></code>: Feature Influence</a></li>
<li><a class="reference internal" href="#module-fatf.transparency.models.submodular_pick"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.models.submodular_pick</span></code>: Submodular Pick</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.transparency.predictions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions</span></code>: Transparency for Predictions</a><ul>
<li><a class="reference internal" href="#module-fatf.transparency.predictions.counterfactuals"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions.counterfactuals</span></code>: Counterfactual Explainers</a><ul>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.transparency.predictions.surrogate_explainers"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions.surrogate_explainers</span></code>: Surrogate Explainers</a></li>
<li><a class="reference internal" href="#module-fatf.transparency.predictions.surrogate_image_explainers"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions.surrogate_image_explainers</span></code>: Surrogate Image Explainers</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.transparency.sklearn"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.sklearn</span></code>: Scikit-learn Explainers</a><ul>
<li><a class="reference internal" href="#module-fatf.transparency.sklearn.tools"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.sklearn.tools</span></code>: Scikit-learn Explainer Tools</a><ul>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.transparency.sklearn.linear_model"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.sklearn.linear_model</span></code>: Linear Model Explainers</a><ul>
</ul>
</li>
</ul>
</li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.vis"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.vis</span></code>: Visualisations</a></li>
<li><a class="reference internal" href="#module-fatf.exceptions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.exceptions</span></code>: Exceptions, Errors and Warnings</a></li>
<li><a class="reference internal" href="#module-fatf.utils"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils</span></code>: Utilities</a><ul>
<li><a class="reference internal" href="#base-classes">Base classes</a></li>
<li><a class="reference internal" href="#module-fatf.utils.array"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.array</span></code>: Array Utilities</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data</span></code>: Data Utilities</a><ul>
<li><a class="reference internal" href="#module-fatf.utils.data.datasets"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.datasets</span></code>: Data Sets</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.tools"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.tools</span></code>: Data Set Tools</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.augmentation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.augmentation</span></code>: Data Set Augmentation</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.instance_augmentation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.instance_augmentation</span></code>: Data Point Augmentation</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.transformation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.transformation</span></code>: Data Set Transformation</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.density"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.density</span></code>: Data Set Density Checking and Estimation</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.discretisation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.discretisation</span></code>: Data Set Discretisation</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.feature_selection"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.feature_selection</span></code>: Data Set Feature Selection</a><ul>
<li><a class="reference internal" href="#module-fatf.utils.data.feature_selection.sklearn"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.feature_selection.sklearn</span></code>: sklearn Feature Selection</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.utils.data.occlusion"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.occlusion</span></code>: Image Occlusion</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.segmentation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.segmentation</span></code>: Image Segmentation</a><ul>
</ul>
</li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.utils.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.models</span></code>: Models Utilities</a><ul>
<li><a class="reference internal" href="#module-fatf.utils.models.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.models.models</span></code>: Example Models</a></li>
<li><a class="reference internal" href="#module-fatf.utils.models.processing"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.models.processing</span></code>: Model Processing</a></li>
<li><a class="reference internal" href="#module-fatf.utils.models.validation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.models.validation</span></code>: Model Validation Tools</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.utils.distances"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.distances</span></code>: Distances and Distance Utilities</a></li>
<li><a class="reference internal" href="#module-fatf.utils.kernels"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.kernels</span></code>: Kernel Functions and Kernel Utilities</a></li>
<li><a class="reference internal" href="#module-fatf.utils.metrics"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.metrics</span></code>: Performance Metrics and Utilities</a><ul>
<li><a class="reference internal" href="#module-fatf.utils.metrics.metrics"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.metrics.metrics</span></code>: Basic Metrics</a></li>
<li><a class="reference internal" href="#module-fatf.utils.metrics.subgroup_metrics"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.metrics.subgroup_metrics</span></code>: Metrics for Sub-Populations</a></li>
<li><a class="reference internal" href="#module-fatf.utils.metrics.tools"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.metrics.tools</span></code>: Metric Tools</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.utils.transparency"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.transparency</span></code>: Transparency Utilities</a><ul>
<li><a class="reference internal" href="#module-fatf.utils.transparency.explainers"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.transparency.explainers</span></code>: Explainer Utilities</a><ul>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.utils.transparency.surrogate_evaluation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.transparency.surrogate_evaluation</span></code>: Surrogates Evaluation</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.utils.tools"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.tools</span></code>: FAT Forensics Tools</a></li>
<li><a class="reference internal" href="#module-fatf.utils.validation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.validation</span></code>: FAT Forensics Validation Functions</a></li>
<li><a class="reference internal" href="#module-fatf.utils.testing"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.testing</span></code>: Testing Utilities</a><ul>
<li><a class="reference internal" href="#constants">Constants</a></li>
<li><a class="reference internal" href="#classes">Classes</a></li>
<li><a class="reference internal" href="#functions">Functions</a></li>
</ul>
</li>
</ul>
</li>
<li><a class="reference internal" href="#fatf-fat-forensics-initialisation-functions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf</span></code>: FAT Forensics Initialisation Functions</a></li>
</ul>
</li>
</ul>
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<ul>
<li><a class="reference internal" href="#">API Reference (0.1.2)</a><ul>
<li><a class="reference internal" href="#fat-forensics">FAT Forensics</a></li>
<li><a class="reference internal" href="#module-fatf.fairness"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness</span></code>: Fairness</a><ul>
<li><a class="reference internal" href="#module-fatf.fairness.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.data</span></code>: Fairness for Data</a></li>
<li><a class="reference internal" href="#module-fatf.fairness.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.models</span></code>: Fairness for Models</a></li>
<li><a class="reference internal" href="#module-fatf.fairness.predictions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.predictions</span></code>: Fairness for Predictions</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.accountability"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.accountability</span></code>: Accountability</a><ul>
<li><a class="reference internal" href="#module-fatf.accountability.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.accountability.data</span></code>: Accountability for Data</a></li>
<li><a class="reference internal" href="#module-fatf.accountability.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.accountability.models</span></code>: Accountability for Models</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.transparency"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency</span></code>: Transparency</a><ul>
<li><a class="reference internal" href="#module-fatf.transparency.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.data</span></code>: Transparency for Data</a></li>
<li><a class="reference internal" href="#module-fatf.transparency.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.models</span></code>: Transparency for Models</a><ul>
<li><a class="reference internal" href="#module-fatf.transparency.models.feature_influence"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.models.feature_influence</span></code>: Feature Influence</a></li>
<li><a class="reference internal" href="#module-fatf.transparency.models.submodular_pick"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.models.submodular_pick</span></code>: Submodular Pick</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.transparency.predictions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions</span></code>: Transparency for Predictions</a><ul>
<li><a class="reference internal" href="#module-fatf.transparency.predictions.counterfactuals"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions.counterfactuals</span></code>: Counterfactual Explainers</a><ul>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.transparency.predictions.surrogate_explainers"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions.surrogate_explainers</span></code>: Surrogate Explainers</a></li>
<li><a class="reference internal" href="#module-fatf.transparency.predictions.surrogate_image_explainers"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions.surrogate_image_explainers</span></code>: Surrogate Image Explainers</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.transparency.sklearn"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.sklearn</span></code>: Scikit-learn Explainers</a><ul>
<li><a class="reference internal" href="#module-fatf.transparency.sklearn.tools"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.sklearn.tools</span></code>: Scikit-learn Explainer Tools</a><ul>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.transparency.sklearn.linear_model"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.sklearn.linear_model</span></code>: Linear Model Explainers</a><ul>
</ul>
</li>
</ul>
</li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.vis"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.vis</span></code>: Visualisations</a></li>
<li><a class="reference internal" href="#module-fatf.exceptions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.exceptions</span></code>: Exceptions, Errors and Warnings</a></li>
<li><a class="reference internal" href="#module-fatf.utils"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils</span></code>: Utilities</a><ul>
<li><a class="reference internal" href="#base-classes">Base classes</a></li>
<li><a class="reference internal" href="#module-fatf.utils.array"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.array</span></code>: Array Utilities</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data</span></code>: Data Utilities</a><ul>
<li><a class="reference internal" href="#module-fatf.utils.data.datasets"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.datasets</span></code>: Data Sets</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.tools"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.tools</span></code>: Data Set Tools</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.augmentation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.augmentation</span></code>: Data Set Augmentation</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.instance_augmentation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.instance_augmentation</span></code>: Data Point Augmentation</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.transformation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.transformation</span></code>: Data Set Transformation</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.density"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.density</span></code>: Data Set Density Checking and Estimation</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.discretisation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.discretisation</span></code>: Data Set Discretisation</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.feature_selection"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.feature_selection</span></code>: Data Set Feature Selection</a><ul>
<li><a class="reference internal" href="#module-fatf.utils.data.feature_selection.sklearn"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.feature_selection.sklearn</span></code>: sklearn Feature Selection</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.utils.data.occlusion"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.occlusion</span></code>: Image Occlusion</a></li>
<li><a class="reference internal" href="#module-fatf.utils.data.segmentation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.segmentation</span></code>: Image Segmentation</a><ul>
</ul>
</li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.utils.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.models</span></code>: Models Utilities</a><ul>
<li><a class="reference internal" href="#module-fatf.utils.models.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.models.models</span></code>: Example Models</a></li>
<li><a class="reference internal" href="#module-fatf.utils.models.processing"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.models.processing</span></code>: Model Processing</a></li>
<li><a class="reference internal" href="#module-fatf.utils.models.validation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.models.validation</span></code>: Model Validation Tools</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.utils.distances"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.distances</span></code>: Distances and Distance Utilities</a></li>
<li><a class="reference internal" href="#module-fatf.utils.kernels"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.kernels</span></code>: Kernel Functions and Kernel Utilities</a></li>
<li><a class="reference internal" href="#module-fatf.utils.metrics"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.metrics</span></code>: Performance Metrics and Utilities</a><ul>
<li><a class="reference internal" href="#module-fatf.utils.metrics.metrics"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.metrics.metrics</span></code>: Basic Metrics</a></li>
<li><a class="reference internal" href="#module-fatf.utils.metrics.subgroup_metrics"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.metrics.subgroup_metrics</span></code>: Metrics for Sub-Populations</a></li>
<li><a class="reference internal" href="#module-fatf.utils.metrics.tools"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.metrics.tools</span></code>: Metric Tools</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.utils.transparency"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.transparency</span></code>: Transparency Utilities</a><ul>
<li><a class="reference internal" href="#module-fatf.utils.transparency.explainers"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.transparency.explainers</span></code>: Explainer Utilities</a><ul>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.utils.transparency.surrogate_evaluation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.transparency.surrogate_evaluation</span></code>: Surrogates Evaluation</a></li>
</ul>
</li>
<li><a class="reference internal" href="#module-fatf.utils.tools"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.tools</span></code>: FAT Forensics Tools</a></li>
<li><a class="reference internal" href="#module-fatf.utils.validation"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.validation</span></code>: FAT Forensics Validation Functions</a></li>
<li><a class="reference internal" href="#module-fatf.utils.testing"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.testing</span></code>: Testing Utilities</a><ul>
<li><a class="reference internal" href="#constants">Constants</a></li>
<li><a class="reference internal" href="#classes">Classes</a></li>
<li><a class="reference internal" href="#functions">Functions</a></li>
</ul>
</li>
</ul>
</li>
<li><a class="reference internal" href="#fatf-fat-forensics-initialisation-functions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf</span></code>: FAT Forensics Initialisation Functions</a></li>
</ul>
</li>
</ul>
</div>
</div>
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<section id="api-reference-version">
<span id="api-ref"></span><h1>API Reference (0.1.2)<a class="headerlink" href="#api-reference-version" title="Permalink to this headline">¶</a></h1>
<p>This is the class and function reference of FAT Forensics. Please refer to
the <a class="reference internal" href="user_guide/index.html#user-guide"><span class="std std-ref">full user guide</span></a> for further details, as the class and
function raw specifications may not be enough to give full guidelines on their
uses.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>The package is designed to work with both <strong>classic</strong> and <strong>structured</strong>
numpy arrays. The latter is introduced to help manage numpy arrays holding
vanila categorical features. Please see the
<a class="reference internal" href="sphinx_gallery_auto/fairness/xmpl_fairness_data_measure.html#sphx-glr-sphinx-gallery-auto-fairness-xmpl-fairness-data-measure-py"><span class="std std-ref">Measuring Fairness of a Data Set</span></a>
and
<a class="reference internal" href="sphinx_gallery_auto/fairness/xmpl_fairness_models_measure.html#sphx-glr-sphinx-gallery-auto-fairness-xmpl-fairness-models-measure-py"><span class="std std-ref">Measuring Fairness of a Predictive Model – Disparate Impact</span></a>
examples to see how the package can be used with a structured numpy array.</p>
</div>
<span class="target" id="module-fatf"></span><section id="fat-forensics">
<h2>FAT Forensics<a class="headerlink" href="#fat-forensics" title="Permalink to this headline">¶</a></h2>
<p>FAT Forensics is a Python module integrating a variety of fairness,
accountability (security, privacy) and transparency (explainability,
interpretability) approaches to assess social impact of artificial
intelligence systems.</p>
</section>
<hr class="docutils" />
<section id="module-fatf.fairness">
<span id="fatf-fairness-fairness"></span><span id="fairness-ref"></span><h2><a class="reference internal" href="#module-fatf.fairness" title="fatf.fairness"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness</span></code></a>: Fairness<a class="headerlink" href="#module-fatf.fairness" title="Permalink to this headline">¶</a></h2>
<p>The <a class="reference internal" href="#module-fatf.fairness" title="fatf.fairness"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness</span></code></a> module implements a variety of fairness algorithms.</p>
<p>This module holds a variety of techniques that can be used to assess
<em>fairness</em> of artificial intelligence pipelines and the machine
learning process: <em>data</em> (<a class="reference internal" href="#module-fatf.fairness.data" title="fatf.fairness.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.data</span></code></a>), <em>models</em>
(<a class="reference internal" href="#module-fatf.fairness.models" title="fatf.fairness.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.models</span></code></a>) and <em>predictions</em>
(<a class="reference internal" href="#module-fatf.fairness.predictions" title="fatf.fairness.predictions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.predictions</span></code></a>).</p>
<section id="module-fatf.fairness.data">
<span id="fatf-fairness-data-fairness-for-data"></span><h3><a class="reference internal" href="#module-fatf.fairness.data" title="fatf.fairness.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.data</span></code></a>: Fairness for Data<a class="headerlink" href="#module-fatf.fairness.data" title="Permalink to this headline">¶</a></h3>
<p>The <a class="reference internal" href="#module-fatf.fairness.data" title="fatf.fairness.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.data</span></code></a> module implements fairness algorithms for data.</p>
<span class="target" id="module-fatf.fairness.data.measures"></span><table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.fairness.data.measures.systemic_bias.html#fatf.fairness.data.measures.systemic_bias" title="fatf.fairness.data.measures.systemic_bias"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.systemic_bias</span></code></a></p></td>
<td><p>Checks for systemic bias in a dataset.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.fairness.data.measures.systemic_bias_check.html#fatf.fairness.data.measures.systemic_bias_check" title="fatf.fairness.data.measures.systemic_bias_check"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.systemic_bias_check</span></code></a></p></td>
<td><p>Indicates whether a dataset has a systemic bias.</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-fatf.fairness.models">
<span id="fatf-fairness-models-fairness-for-models"></span><h3><a class="reference internal" href="#module-fatf.fairness.models" title="fatf.fairness.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.models</span></code></a>: Fairness for Models<a class="headerlink" href="#module-fatf.fairness.models" title="Permalink to this headline">¶</a></h3>
<p>The <a class="reference internal" href="#module-fatf.fairness.models" title="fatf.fairness.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.models</span></code></a> module holds fairness algorithms for models.</p>
<span class="target" id="module-fatf.fairness.models.measures"></span><table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.fairness.models.measures.disparate_impact.html#fatf.fairness.models.measures.disparate_impact" title="fatf.fairness.models.measures.disparate_impact"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.disparate_impact</span></code></a></p></td>
<td><p>Calculates selected disparate impact grid for a data set.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.fairness.models.measures.disparate_impact_indexed.html#fatf.fairness.models.measures.disparate_impact_indexed" title="fatf.fairness.models.measures.disparate_impact_indexed"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.disparate_impact_indexed</span></code></a></p></td>
<td><p>Calculates selected disparate impact grid for indexed data.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.fairness.models.measures.disparate_impact_check.html#fatf.fairness.models.measures.disparate_impact_check" title="fatf.fairness.models.measures.disparate_impact_check"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.disparate_impact_check</span></code></a></p></td>
<td><p>Checks if any sub-population pair violates chosen disparate impact measure.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.fairness.models.measures.demographic_parity.html#fatf.fairness.models.measures.demographic_parity" title="fatf.fairness.models.measures.demographic_parity"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.demographic_parity</span></code></a></p></td>
<td><p>Checks for demographic parity between all of the sub-populations.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.fairness.models.measures.equal_opportunity.html#fatf.fairness.models.measures.equal_opportunity" title="fatf.fairness.models.measures.equal_opportunity"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.equal_opportunity</span></code></a></p></td>
<td><p>Checks for equal opportunity between all of the sub-populations.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.fairness.models.measures.equal_accuracy.html#fatf.fairness.models.measures.equal_accuracy" title="fatf.fairness.models.measures.equal_accuracy"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.equal_accuracy</span></code></a></p></td>
<td><p>Checks if accuracy difference of all grouping pairs is within tolerance.</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-fatf.fairness.predictions">
<span id="fatf-fairness-predictions-fairness-for-predictions"></span><h3><a class="reference internal" href="#module-fatf.fairness.predictions" title="fatf.fairness.predictions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.predictions</span></code></a>: Fairness for Predictions<a class="headerlink" href="#module-fatf.fairness.predictions" title="Permalink to this headline">¶</a></h3>
<p>The <a class="reference internal" href="#module-fatf.fairness.predictions" title="fatf.fairness.predictions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.fairness.predictions</span></code></a> module houses fairness for predictions.</p>
<span class="target" id="module-fatf.fairness.predictions.measures"></span><table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.fairness.predictions.measures.counterfactual_fairness.html#fatf.fairness.predictions.measures.counterfactual_fairness" title="fatf.fairness.predictions.measures.counterfactual_fairness"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.counterfactual_fairness</span></code></a></p></td>
<td><p>Checks counterfactual fairness of a prediction given a model.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.fairness.predictions.measures.counterfactual_fairness_check.html#fatf.fairness.predictions.measures.counterfactual_fairness_check" title="fatf.fairness.predictions.measures.counterfactual_fairness_check"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.counterfactual_fairness_check</span></code></a></p></td>
<td><p>Checks for counterfactual fairness using a counterfactual fairness arrays.</p></td>
</tr>
</tbody>
</table>
</section>
</section>
<section id="module-fatf.accountability">
<span id="fatf-accountability-accountability"></span><span id="accountability-ref"></span><h2><a class="reference internal" href="#module-fatf.accountability" title="fatf.accountability"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.accountability</span></code></a>: Accountability<a class="headerlink" href="#module-fatf.accountability" title="Permalink to this headline">¶</a></h2>
<p>The <a class="reference internal" href="#module-fatf.accountability" title="fatf.accountability"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.accountability</span></code></a> module holds a range of accountability methods.</p>
<p>This module holds a variety of techniques that can be used to assess <em>privacy</em>,
<em>security</em> and <em>robustness</em> of artificial intelligence pipelines and the
machine learning process: <em>data</em>, <em>models</em> and <em>predictions</em>.</p>
<section id="module-fatf.accountability.data">
<span id="fatf-accountability-data-accountability-for-data"></span><h3><a class="reference internal" href="#module-fatf.accountability.data" title="fatf.accountability.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.accountability.data</span></code></a>: Accountability for Data<a class="headerlink" href="#module-fatf.accountability.data" title="Permalink to this headline">¶</a></h3>
<p>The <a class="reference internal" href="#module-fatf.accountability.data" title="fatf.accountability.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.accountability.data</span></code></a> module implements accountability algorithms
for data.</p>
<span class="target" id="module-fatf.accountability.data.measures"></span><table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.accountability.data.measures.sampling_bias.html#fatf.accountability.data.measures.sampling_bias" title="fatf.accountability.data.measures.sampling_bias"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.sampling_bias</span></code></a></p></td>
<td><p>Computes information needed for evaluating and remedying sampling bias.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.accountability.data.measures.sampling_bias_indexed.html#fatf.accountability.data.measures.sampling_bias_indexed" title="fatf.accountability.data.measures.sampling_bias_indexed"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.sampling_bias_indexed</span></code></a></p></td>
<td><p>Computes information needed for evaluating and remedying sampling bias.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.accountability.data.measures.sampling_bias_grid_check.html#fatf.accountability.data.measures.sampling_bias_grid_check" title="fatf.accountability.data.measures.sampling_bias_grid_check"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.sampling_bias_grid_check</span></code></a></p></td>
<td><p>Checks for a pairwise sampling bias based on the provided threshold.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.accountability.data.measures.sampling_bias_check.html#fatf.accountability.data.measures.sampling_bias_check" title="fatf.accountability.data.measures.sampling_bias_check"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.sampling_bias_check</span></code></a></p></td>
<td><p>Checks for a pairwise sampling bias based on the provided threshold.</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-fatf.accountability.models">
<span id="fatf-accountability-models-accountability-for-models"></span><h3><a class="reference internal" href="#module-fatf.accountability.models" title="fatf.accountability.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.accountability.models</span></code></a>: Accountability for Models<a class="headerlink" href="#module-fatf.accountability.models" title="Permalink to this headline">¶</a></h3>
<p>The <a class="reference internal" href="#module-fatf.accountability.models" title="fatf.accountability.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.accountability.models</span></code></a> module holds accountability algorithms
for models.</p>
<span class="target" id="module-fatf.accountability.models.measures"></span><table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.accountability.models.measures.systematic_performance_bias.html#fatf.accountability.models.measures.systematic_performance_bias" title="fatf.accountability.models.measures.systematic_performance_bias"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.systematic_performance_bias</span></code></a></p></td>
<td><p>Checks for a systematic bias in provided predictive performance values.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.accountability.models.measures.systematic_performance_bias_grid.html#fatf.accountability.models.measures.systematic_performance_bias_grid" title="fatf.accountability.models.measures.systematic_performance_bias_grid"><code class="xref py py-obj docutils literal notranslate"><span class="pre">measures.systematic_performance_bias_grid</span></code></a></p></td>
<td><p>Checks for pairwise systematic bias in group-wise predictive performance.</p></td>
</tr>
</tbody>
</table>
</section>
</section>
<section id="module-fatf.transparency">
<span id="fatf-transparency-transparency"></span><span id="transparency-ref"></span><h2><a class="reference internal" href="#module-fatf.transparency" title="fatf.transparency"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency</span></code></a>: Transparency<a class="headerlink" href="#module-fatf.transparency" title="Permalink to this headline">¶</a></h2>
<p>The <a class="reference internal" href="#module-fatf.transparency" title="fatf.transparency"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency</span></code></a> module implements various transparency algorithms.</p>
<p>This module holds a variety of techniques that can be used to assess
<em>explainability</em> and <em>interpretability</em> of artificial intelligence pipelines
and the machine learning process: <em>data</em>, <em>models</em> and <em>predictions</em>.</p>
<section id="module-fatf.transparency.data">
<span id="fatf-transparency-data-transparency-for-data"></span><h3><a class="reference internal" href="#module-fatf.transparency.data" title="fatf.transparency.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.data</span></code></a>: Transparency for Data<a class="headerlink" href="#module-fatf.transparency.data" title="Permalink to this headline">¶</a></h3>
<p>The <a class="reference internal" href="#module-fatf.transparency.data" title="fatf.transparency.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.data</span></code></a> module holds data transparency algorithms.</p>
<span class="target" id="module-fatf.transparency.data.describe_functions"></span><table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.data.describe_functions.describe_array.html#fatf.transparency.data.describe_functions.describe_array" title="fatf.transparency.data.describe_functions.describe_array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">describe_functions.describe_array</span></code></a></p></td>
<td><p>Describes categorical (textual) and numerical columns in the input array.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.transparency.data.describe_functions.describe_numerical_array.html#fatf.transparency.data.describe_functions.describe_numerical_array" title="fatf.transparency.data.describe_functions.describe_numerical_array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">describe_functions.describe_numerical_array</span></code></a></p></td>
<td><p>Describes a numerical numpy array with basic statistics.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.data.describe_functions.describe_categorical_array.html#fatf.transparency.data.describe_functions.describe_categorical_array" title="fatf.transparency.data.describe_functions.describe_categorical_array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">describe_functions.describe_categorical_array</span></code></a></p></td>
<td><p>Describes a categorical numpy array with basic statistics.</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-fatf.transparency.models">
<span id="fatf-transparency-models-transparency-for-models"></span><h3><a class="reference internal" href="#module-fatf.transparency.models" title="fatf.transparency.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.models</span></code></a>: Transparency for Models<a class="headerlink" href="#module-fatf.transparency.models" title="Permalink to this headline">¶</a></h3>
<p>The <a class="reference internal" href="#module-fatf.transparency.models" title="fatf.transparency.models"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.models</span></code></a> module holds models transparency functions.</p>
<section id="module-fatf.transparency.models.feature_influence">
<span id="fatf-transparency-models-feature-influence-feature-influence"></span><h4><a class="reference internal" href="#module-fatf.transparency.models.feature_influence" title="fatf.transparency.models.feature_influence"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.models.feature_influence</span></code></a>: Feature Influence<a class="headerlink" href="#module-fatf.transparency.models.feature_influence" title="Permalink to this headline">¶</a></h4>
<p>The <a class="reference internal" href="#module-fatf.transparency.models.feature_influence" title="fatf.transparency.models.feature_influence"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.models.feature_influence</span></code></a> module holds functions
for calculating feature influence for predictive models.</p>
<p>This module implements Partial Dependence (PD) and Individual Conditional
Expectation (ICE) – model agnostic feature influence measurements.</p>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.models.feature_influence.individual_conditional_expectation.html#fatf.transparency.models.feature_influence.individual_conditional_expectation" title="fatf.transparency.models.feature_influence.individual_conditional_expectation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">feature_influence.individual_conditional_expectation</span></code></a></p></td>
<td><p>Calculates Individual Conditional Expectation for a selected feature.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.transparency.models.feature_influence.merge_ice_arrays.html#fatf.transparency.models.feature_influence.merge_ice_arrays" title="fatf.transparency.models.feature_influence.merge_ice_arrays"><code class="xref py py-obj docutils literal notranslate"><span class="pre">feature_influence.merge_ice_arrays</span></code></a></p></td>
<td><p>Merges multiple Individual Conditional Expectation arrays.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.models.feature_influence.partial_dependence_ice.html#fatf.transparency.models.feature_influence.partial_dependence_ice" title="fatf.transparency.models.feature_influence.partial_dependence_ice"><code class="xref py py-obj docutils literal notranslate"><span class="pre">feature_influence.partial_dependence_ice</span></code></a></p></td>
<td><p>Calculates Partial Dependence based on Individual Conditional Expectations.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.transparency.models.feature_influence.partial_dependence.html#fatf.transparency.models.feature_influence.partial_dependence" title="fatf.transparency.models.feature_influence.partial_dependence"><code class="xref py py-obj docutils literal notranslate"><span class="pre">feature_influence.partial_dependence</span></code></a></p></td>
<td><p>Calculates Partial Dependence for a selected feature.</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-fatf.transparency.models.submodular_pick">
<span id="fatf-transparency-models-submodular-pick-submodular-pick"></span><h4><a class="reference internal" href="#module-fatf.transparency.models.submodular_pick" title="fatf.transparency.models.submodular_pick"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.models.submodular_pick</span></code></a>: Submodular Pick<a class="headerlink" href="#module-fatf.transparency.models.submodular_pick" title="Permalink to this headline">¶</a></h4>
<p>The <a class="reference internal" href="#module-fatf.transparency.models.submodular_pick" title="fatf.transparency.models.submodular_pick"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.models.submodular_pick</span></code></a> module implements the
submodular pick algorithm proposed by <a class="reference internal" href="#ra376fa965786-ribeiro2016why" id="id1"><span>[Ra376fa965786-RIBEIRO2016WHY]</span></a>.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 0.1.1.</span></p>
</div>
<dl class="citation">
<dt class="label" id="ra376fa965786-ribeiro2016why"><span class="brackets"><a class="fn-backref" href="#id1">Ra376fa965786-RIBEIRO2016WHY</a></span></dt>
<dd><p>Ribeiro, M.T., Singh, S. and Guestrin, C., 2016,
August. Why should I trust you?: Explaining the predictions of any
classifier. In Proceedings of the 22nd ACM SIGKDD international
conference on knowledge discovery and data mining (pp. 1135-1144). ACM.</p>
</dd>
</dl>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.models.submodular_pick.submodular_pick.html#fatf.transparency.models.submodular_pick.submodular_pick" title="fatf.transparency.models.submodular_pick.submodular_pick"><code class="xref py py-obj docutils literal notranslate"><span class="pre">submodular_pick.submodular_pick</span></code></a></p></td>
<td><p>Applies submodular pick to explanations of a given subset of data.</p></td>
</tr>
</tbody>
</table>
</section>
</section>
<section id="module-fatf.transparency.predictions">
<span id="fatf-transparency-predictions-transparency-for-predictions"></span><h3><a class="reference internal" href="#module-fatf.transparency.predictions" title="fatf.transparency.predictions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions</span></code></a>: Transparency for Predictions<a class="headerlink" href="#module-fatf.transparency.predictions" title="Permalink to this headline">¶</a></h3>
<p>The <a class="reference internal" href="#module-fatf.transparency.predictions" title="fatf.transparency.predictions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions</span></code></a> module holds predictions transparency
functions.</p>
<section id="module-fatf.transparency.predictions.counterfactuals">
<span id="fatf-transparency-predictions-counterfactuals-counterfactual-explainers"></span><h4><a class="reference internal" href="#module-fatf.transparency.predictions.counterfactuals" title="fatf.transparency.predictions.counterfactuals"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions.counterfactuals</span></code></a>: Counterfactual Explainers<a class="headerlink" href="#module-fatf.transparency.predictions.counterfactuals" title="Permalink to this headline">¶</a></h4>
<p>The <a class="reference internal" href="#module-fatf.transparency.predictions.counterfactuals" title="fatf.transparency.predictions.counterfactuals"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions.counterfactuals</span></code></a> module implements
counterfactual explainers for predictions.</p>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.predictions.counterfactuals.CounterfactualExplainer.html#fatf.transparency.predictions.counterfactuals.CounterfactualExplainer" title="fatf.transparency.predictions.counterfactuals.CounterfactualExplainer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">counterfactuals.CounterfactualExplainer</span></code></a></p></td>
<td><p>Generates counterfactual explanations of black-box classifier predictions.</p></td>
</tr>
</tbody>
</table>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.predictions.counterfactuals.textualise_counterfactuals.html#fatf.transparency.predictions.counterfactuals.textualise_counterfactuals" title="fatf.transparency.predictions.counterfactuals.textualise_counterfactuals"><code class="xref py py-obj docutils literal notranslate"><span class="pre">counterfactuals.textualise_counterfactuals</span></code></a></p></td>
<td><p>Translates a counterfactuals array into a textual description.</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-fatf.transparency.predictions.surrogate_explainers">
<span id="fatf-transparency-predictions-surrogate-explainers-surrogate-explainers"></span><h4><a class="reference internal" href="#module-fatf.transparency.predictions.surrogate_explainers" title="fatf.transparency.predictions.surrogate_explainers"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions.surrogate_explainers</span></code></a>: Surrogate Explainers<a class="headerlink" href="#module-fatf.transparency.predictions.surrogate_explainers" title="Permalink to this headline">¶</a></h4>
<div class="versionadded">
<p><span class="versionmodified added">New in version 0.0.2.</span></p>
</div>
<p>The <a class="reference internal" href="#module-fatf.transparency.predictions.surrogate_explainers" title="fatf.transparency.predictions.surrogate_explainers"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions.surrogate_explainers</span></code></a> module implements
example surrogate explainers.</p>
<p>Guidelines and tips for building custom surrogate explainers for various
types of data (tabular, image and text) can be found in the <a class="reference internal" href="how_to/index.html#how-to-guide"><span class="std std-ref">How-to Guides</span></a>
part of the documentation:</p>
<ul class="simple">
<li><p><a class="reference internal" href="how_to/transparency/tabular-surrogates.html#how-to-tabular-surrogates"><span class="std std-ref">How to build LIME yourself (bLIMEy) – Surrogate Tabular Explainers</span></a>.</p></li>
</ul>
<p>The <code class="docutils literal notranslate"><span class="pre">scikit-learn</span></code> package is required for the surrogate tree and linear
model (LIME) explainers to work. When importing this module with
<code class="docutils literal notranslate"><span class="pre">scikit-learn</span></code> missing, the user will only be warned about disabling this
functionality not being available and the two explainers will
be disabled to allow using the abstract SurrogateTabularExplainer without
the <code class="docutils literal notranslate"><span class="pre">scikit-learn</span></code> package installed.</p>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.predictions.surrogate_explainers.SurrogateTabularExplainer.html#fatf.transparency.predictions.surrogate_explainers.SurrogateTabularExplainer" title="fatf.transparency.predictions.surrogate_explainers.SurrogateTabularExplainer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">surrogate_explainers.SurrogateTabularExplainer</span></code></a></p></td>
<td><p>An abstract parent class for implementing surrogate explainers.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.transparency.predictions.surrogate_explainers.TabularBlimeyLime.html#fatf.transparency.predictions.surrogate_explainers.TabularBlimeyLime" title="fatf.transparency.predictions.surrogate_explainers.TabularBlimeyLime"><code class="xref py py-obj docutils literal notranslate"><span class="pre">surrogate_explainers.TabularBlimeyLime</span></code></a></p></td>
<td><p>A tabular LIME explainer – a surrogate explainer based on a linear model.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.predictions.surrogate_explainers.TabularBlimeyTree.html#fatf.transparency.predictions.surrogate_explainers.TabularBlimeyTree" title="fatf.transparency.predictions.surrogate_explainers.TabularBlimeyTree"><code class="xref py py-obj docutils literal notranslate"><span class="pre">surrogate_explainers.TabularBlimeyTree</span></code></a></p></td>
<td><p>A surrogate explainer based on a decision tree.</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-fatf.transparency.predictions.surrogate_image_explainers">
<span id="fatf-transparency-predictions-surrogate-image-explainers-surrogate-image-explainers"></span><h4><a class="reference internal" href="#module-fatf.transparency.predictions.surrogate_image_explainers" title="fatf.transparency.predictions.surrogate_image_explainers"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions.surrogate_image_explainers</span></code></a>: Surrogate Image Explainers<a class="headerlink" href="#module-fatf.transparency.predictions.surrogate_image_explainers" title="Permalink to this headline">¶</a></h4>
<p>The <a class="reference internal" href="#module-fatf.transparency.predictions.surrogate_image_explainers" title="fatf.transparency.predictions.surrogate_image_explainers"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.predictions.surrogate_image_explainers</span></code></a> module
implements a bLIMEy version of the LIME surrogate image explainer.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 0.1.1.</span></p>
</div>
<p>The <code class="docutils literal notranslate"><span class="pre">scikit-learn</span></code>, <code class="docutils literal notranslate"><span class="pre">scikit-image</span></code> and <code class="docutils literal notranslate"><span class="pre">Pillow</span></code> packages are required for
the surrogate image explainer to work.</p>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.predictions.surrogate_image_explainers.ImageBlimeyLime.html#fatf.transparency.predictions.surrogate_image_explainers.ImageBlimeyLime" title="fatf.transparency.predictions.surrogate_image_explainers.ImageBlimeyLime"><code class="xref py py-obj docutils literal notranslate"><span class="pre">surrogate_image_explainers.ImageBlimeyLime</span></code></a></p></td>
<td><p>Implements a surrogate image explainer equivalent to LIME.</p></td>
</tr>
</tbody>
</table>
</section>
</section>
<section id="module-fatf.transparency.sklearn">
<span id="fatf-transparency-sklearn-scikit-learn-explainers"></span><h3><a class="reference internal" href="#module-fatf.transparency.sklearn" title="fatf.transparency.sklearn"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.sklearn</span></code></a>: Scikit-learn Explainers<a class="headerlink" href="#module-fatf.transparency.sklearn" title="Permalink to this headline">¶</a></h3>
<p>The <a class="reference internal" href="#module-fatf.transparency.sklearn" title="fatf.transparency.sklearn"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.sklearn</span></code></a> module implements scikit-learn explainers.</p>
<p><strong>This module requires the scikit-learn package to be installed.</strong></p>
<section id="module-fatf.transparency.sklearn.tools">
<span id="fatf-transparency-sklearn-tools-scikit-learn-explainer-tools"></span><h4><a class="reference internal" href="#module-fatf.transparency.sklearn.tools" title="fatf.transparency.sklearn.tools"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.sklearn.tools</span></code></a>: Scikit-learn Explainer Tools<a class="headerlink" href="#module-fatf.transparency.sklearn.tools" title="Permalink to this headline">¶</a></h4>
<div class="versionadded">
<p><span class="versionmodified added">New in version 0.0.2.</span></p>
</div>
<p>The <a class="reference internal" href="#module-fatf.transparency.sklearn.tools" title="fatf.transparency.sklearn.tools"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.sklearn.tools</span></code></a> module implements a base
scikit-learn explainer.</p>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.sklearn.tools.SKLearnExplainer.html#fatf.transparency.sklearn.tools.SKLearnExplainer" title="fatf.transparency.sklearn.tools.SKLearnExplainer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tools.SKLearnExplainer</span></code></a></p></td>
<td><p>Implements a base scikit-learn model explainer class.</p></td>
</tr>
</tbody>
</table>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.sklearn.tools.is_sklearn_model.html#fatf.transparency.sklearn.tools.is_sklearn_model" title="fatf.transparency.sklearn.tools.is_sklearn_model"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tools.is_sklearn_model</span></code></a></p></td>
<td><p>Checks whether a class instance or a class is a scikit-learn predictor.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.transparency.sklearn.tools.is_sklearn_model_instance.html#fatf.transparency.sklearn.tools.is_sklearn_model_instance" title="fatf.transparency.sklearn.tools.is_sklearn_model_instance"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tools.is_sklearn_model_instance</span></code></a></p></td>
<td><p>Checks whether a class instance (object) is a scikit-learn predictor.</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-fatf.transparency.sklearn.linear_model">
<span id="fatf-transparency-sklearn-linear-model-linear-model-explainers"></span><h4><a class="reference internal" href="#module-fatf.transparency.sklearn.linear_model" title="fatf.transparency.sklearn.linear_model"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.sklearn.linear_model</span></code></a>: Linear Model Explainers<a class="headerlink" href="#module-fatf.transparency.sklearn.linear_model" title="Permalink to this headline">¶</a></h4>
<div class="versionadded">
<p><span class="versionmodified added">New in version 0.0.2.</span></p>
</div>
<p>The <a class="reference internal" href="#module-fatf.transparency.sklearn.linear_model" title="fatf.transparency.sklearn.linear_model"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.transparency.sklearn.linear_model</span></code></a> module implements linear
scikit-learn model explainers.</p>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.sklearn.linear_model.SKLearnLinearModelExplainer.html#fatf.transparency.sklearn.linear_model.SKLearnLinearModelExplainer" title="fatf.transparency.sklearn.linear_model.SKLearnLinearModelExplainer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">linear_model.SKLearnLinearModelExplainer</span></code></a></p></td>
<td><p>A scikit-learn linear model explainer class.</p></td>
</tr>
</tbody>
</table>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.transparency.sklearn.linear_model.linear_classifier_coefficients.html#fatf.transparency.sklearn.linear_model.linear_classifier_coefficients" title="fatf.transparency.sklearn.linear_model.linear_classifier_coefficients"><code class="xref py py-obj docutils literal notranslate"><span class="pre">linear_model.linear_classifier_coefficients</span></code></a></p></td>
<td><p>Extracts coefficients (feature importances) of a linear scikit-learn model.</p></td>
</tr>
</tbody>
</table>
</section>
</section>
</section>
<section id="module-fatf.vis">
<span id="fatf-vis-visualisations"></span><span id="vis-ref"></span><h2><a class="reference internal" href="#module-fatf.vis" title="fatf.vis"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.vis</span></code></a>: Visualisations<a class="headerlink" href="#module-fatf.vis" title="Permalink to this headline">¶</a></h2>
<p>The <a class="reference internal" href="#module-fatf.vis" title="fatf.vis"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.vis</span></code></a> module implements visualisations of various FAT methods.</p>
<p><strong>This module requires the matplotlib package to be installed.</strong></p>
<span class="target" id="module-fatf.vis.feature_influence"></span><span class="target" id="module-fatf.vis.lime"></span><table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.vis.feature_influence.plot_individual_conditional_expectation.html#fatf.vis.feature_influence.plot_individual_conditional_expectation" title="fatf.vis.feature_influence.plot_individual_conditional_expectation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">feature_influence.plot_individual_conditional_expectation</span></code></a></p></td>
<td><p>Plots Individual Conditional Expectation for a selected class.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.vis.feature_influence.plot_partial_dependence.html#fatf.vis.feature_influence.plot_partial_dependence" title="fatf.vis.feature_influence.plot_partial_dependence"><code class="xref py py-obj docutils literal notranslate"><span class="pre">feature_influence.plot_partial_dependence</span></code></a></p></td>
<td><p>Plots Partial Dependence for a selected class.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.vis.lime.plot_lime.html#fatf.vis.lime.plot_lime" title="fatf.vis.lime.plot_lime"><code class="xref py py-obj docutils literal notranslate"><span class="pre">lime.plot_lime</span></code></a></p></td>
<td><p>Plots an importance-based surrogate explanation, e.g., LIME.</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-fatf.exceptions">
<span id="fatf-exceptions-exceptions-errors-and-warnings"></span><span id="exceptions-ref"></span><h2><a class="reference internal" href="#module-fatf.exceptions" title="fatf.exceptions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.exceptions</span></code></a>: Exceptions, Errors and Warnings<a class="headerlink" href="#module-fatf.exceptions" title="Permalink to this headline">¶</a></h2>
<p>The <a class="reference internal" href="#module-fatf.exceptions" title="fatf.exceptions"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.exceptions</span></code></a> module holds custom exceptions, errors and warnings.</p>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.exceptions.FATFException.html#fatf.exceptions.FATFException" title="fatf.exceptions.FATFException"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FATFException</span></code></a></p></td>
<td><p>Base class for FAT Forensics exceptions (inherits from <a class="reference external" href="https://docs.python.org/3/library/exceptions.html#Exception" title="(in Python v3.11)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Exception</span></code></a>).</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.exceptions.IncorrectShapeError.html#fatf.exceptions.IncorrectShapeError" title="fatf.exceptions.IncorrectShapeError"><code class="xref py py-obj docutils literal notranslate"><span class="pre">IncorrectShapeError</span></code></a></p></td>
<td><p>Exception raised when the shape of an array is not what is expected.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.exceptions.IncompatibleExplainerError.html#fatf.exceptions.IncompatibleExplainerError" title="fatf.exceptions.IncompatibleExplainerError"><code class="xref py py-obj docutils literal notranslate"><span class="pre">IncompatibleExplainerError</span></code></a></p></td>
<td><p>Exception raised when an explainer lacks desired functionality.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.exceptions.IncompatibleModelError.html#fatf.exceptions.IncompatibleModelError" title="fatf.exceptions.IncompatibleModelError"><code class="xref py py-obj docutils literal notranslate"><span class="pre">IncompatibleModelError</span></code></a></p></td>
<td><p>Exception raised when a model lacks desired functionality.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.exceptions.UnfittedModelError.html#fatf.exceptions.UnfittedModelError" title="fatf.exceptions.UnfittedModelError"><code class="xref py py-obj docutils literal notranslate"><span class="pre">UnfittedModelError</span></code></a></p></td>
<td><p>Exception raised when a model is unfitted and a fitted one is expected.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.exceptions.PrefittedModelError.html#fatf.exceptions.PrefittedModelError" title="fatf.exceptions.PrefittedModelError"><code class="xref py py-obj docutils literal notranslate"><span class="pre">PrefittedModelError</span></code></a></p></td>
<td><p>Exception raised when a model is fitted and an unfitted one is expected.</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-fatf.utils">
<span id="fatf-utils-utilities"></span><h2><a class="reference internal" href="#module-fatf.utils" title="fatf.utils"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils</span></code></a>: Utilities<a class="headerlink" href="#module-fatf.utils" title="Permalink to this headline">¶</a></h2>
<p>The <a class="reference internal" href="#module-fatf.utils" title="fatf.utils"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils</span></code></a> module includes various utilities.</p>
<p><strong>Developer guide:</strong> See the <a class="reference internal" href="development.html#developers-guide"><span class="std std-ref">Developers Guide</span></a> page for further details.</p>
<section id="base-classes">
<h3>Base classes<a class="headerlink" href="#base-classes" title="Permalink to this headline">¶</a></h3>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.data.augmentation.Augmentation.html#fatf.utils.data.augmentation.Augmentation" title="fatf.utils.data.augmentation.Augmentation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">data.augmentation.Augmentation</span></code></a></p></td>
<td><p>An abstract class for implementing data augmentation methods.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.utils.models.models.Model.html#fatf.utils.models.models.Model" title="fatf.utils.models.models.Model"><code class="xref py py-obj docutils literal notranslate"><span class="pre">models.models.Model</span></code></a></p></td>
<td><p>An abstract class used to implement predictive models.</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-fatf.utils.array">
<span id="fatf-utils-array-array-utilities"></span><h3><a class="reference internal" href="#module-fatf.utils.array" title="fatf.utils.array"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.array</span></code></a>: Array Utilities<a class="headerlink" href="#module-fatf.utils.array" title="Permalink to this headline">¶</a></h3>
<p>The <a class="reference internal" href="#module-fatf.utils.array" title="fatf.utils.array"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.array</span></code></a> module holds array tools and validation functions.</p>
<span class="target" id="module-fatf.utils.array.tools"></span><span class="target" id="module-fatf.utils.array.validation"></span><table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.array.tools.indices_by_type.html#fatf.utils.array.tools.indices_by_type" title="fatf.utils.array.tools.indices_by_type"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tools.indices_by_type</span></code></a></p></td>
<td><p>Identifies indices of columns with numerical and non-numerical values.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.utils.array.tools.get_invalid_indices.html#fatf.utils.array.tools.get_invalid_indices" title="fatf.utils.array.tools.get_invalid_indices"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tools.get_invalid_indices</span></code></a></p></td>
<td><p>Returns a numpy array with column indices that the input array is missing.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.array.tools.are_indices_valid.html#fatf.utils.array.tools.are_indices_valid" title="fatf.utils.array.tools.are_indices_valid"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tools.are_indices_valid</span></code></a></p></td>
<td><p>Checks whether all the input <code class="docutils literal notranslate"><span class="pre">indices</span></code> are valid for the input <code class="docutils literal notranslate"><span class="pre">array</span></code>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.utils.array.tools.generalise_dtype.html#fatf.utils.array.tools.generalise_dtype" title="fatf.utils.array.tools.generalise_dtype"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tools.generalise_dtype</span></code></a></p></td>
<td><p>Finds the more general type of the two given.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.array.tools.structured_to_unstructured_row.html#fatf.utils.array.tools.structured_to_unstructured_row" title="fatf.utils.array.tools.structured_to_unstructured_row"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tools.structured_to_unstructured_row</span></code></a></p></td>
<td><p>Calls either local or numpy’s <code class="docutils literal notranslate"><span class="pre">structured_to_unstructured</span></code> function.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.utils.array.tools.structured_to_unstructured.html#fatf.utils.array.tools.structured_to_unstructured" title="fatf.utils.array.tools.structured_to_unstructured"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tools.structured_to_unstructured</span></code></a></p></td>
<td><p>Calls either local or numpy’s <code class="docutils literal notranslate"><span class="pre">structured_to_unstructured</span></code> function.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.array.tools.as_unstructured.html#fatf.utils.array.tools.as_unstructured" title="fatf.utils.array.tools.as_unstructured"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tools.as_unstructured</span></code></a></p></td>
<td><p>Converts an array like object into an unstructured array.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.is_numerical_dtype.html#fatf.utils.array.validation.is_numerical_dtype" title="fatf.utils.array.validation.is_numerical_dtype"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.is_numerical_dtype</span></code></a></p></td>
<td><p>Determines whether a numpy dtype object is of numerical type.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.is_textual_dtype.html#fatf.utils.array.validation.is_textual_dtype" title="fatf.utils.array.validation.is_textual_dtype"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.is_textual_dtype</span></code></a></p></td>
<td><p>Determines whether a numpy dtype object is of textual type.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.is_base_dtype.html#fatf.utils.array.validation.is_base_dtype" title="fatf.utils.array.validation.is_base_dtype"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.is_base_dtype</span></code></a></p></td>
<td><p>Determines whether a numpy dtype object is one of base types.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.is_flat_dtype.html#fatf.utils.array.validation.is_flat_dtype" title="fatf.utils.array.validation.is_flat_dtype"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.is_flat_dtype</span></code></a></p></td>
<td><p>Determines whether a numpy dtype object is flat.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.are_similar_dtypes.html#fatf.utils.array.validation.are_similar_dtypes" title="fatf.utils.array.validation.are_similar_dtypes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.are_similar_dtypes</span></code></a></p></td>
<td><p>Checks whether two numpy dtypes are similar.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.are_similar_dtype_arrays.html#fatf.utils.array.validation.are_similar_dtype_arrays" title="fatf.utils.array.validation.are_similar_dtype_arrays"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.are_similar_dtype_arrays</span></code></a></p></td>
<td><p>Determines whether two numpy array-like object have a similar data type.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.is_numerical_array.html#fatf.utils.array.validation.is_numerical_array" title="fatf.utils.array.validation.is_numerical_array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.is_numerical_array</span></code></a></p></td>
<td><p>Determines whether a numpy array-like object has a numerical data type.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.is_textual_array.html#fatf.utils.array.validation.is_textual_array" title="fatf.utils.array.validation.is_textual_array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.is_textual_array</span></code></a></p></td>
<td><p>Determines whether a numpy array-like object has a textual data type.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.is_base_array.html#fatf.utils.array.validation.is_base_array" title="fatf.utils.array.validation.is_base_array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.is_base_array</span></code></a></p></td>
<td><p>Determines whether a numpy array-like object holds base data types.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.is_1d_array.html#fatf.utils.array.validation.is_1d_array" title="fatf.utils.array.validation.is_1d_array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.is_1d_array</span></code></a></p></td>
<td><p>Determines whether a numpy array-like object is 1-dimensional.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.is_2d_array.html#fatf.utils.array.validation.is_2d_array" title="fatf.utils.array.validation.is_2d_array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.is_2d_array</span></code></a></p></td>
<td><p>Determines whether a numpy array-like object has 2 dimensions.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.is_structured_row.html#fatf.utils.array.validation.is_structured_row" title="fatf.utils.array.validation.is_structured_row"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.is_structured_row</span></code></a></p></td>
<td><p>Determines whether the input is a structured numpy array’s row object.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.is_1d_like.html#fatf.utils.array.validation.is_1d_like" title="fatf.utils.array.validation.is_1d_like"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.is_1d_like</span></code></a></p></td>
<td><p>Checks if the input is either a 1D numpy array or a structured numpy row.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.array.validation.is_structured_array.html#fatf.utils.array.validation.is_structured_array" title="fatf.utils.array.validation.is_structured_array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validation.is_structured_array</span></code></a></p></td>
<td><p>Determines whether a numpy array-like object is a structured array.</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-fatf.utils.data">
<span id="fatf-utils-data-data-utilities"></span><h3><a class="reference internal" href="#module-fatf.utils.data" title="fatf.utils.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data</span></code></a>: Data Utilities<a class="headerlink" href="#module-fatf.utils.data" title="Permalink to this headline">¶</a></h3>
<p>The <a class="reference internal" href="#module-fatf.utils.data" title="fatf.utils.data"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data</span></code></a> module holds data tools and data sets.</p>
<section id="module-fatf.utils.data.datasets">
<span id="fatf-utils-data-datasets-data-sets"></span><h4><a class="reference internal" href="#module-fatf.utils.data.datasets" title="fatf.utils.data.datasets"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.datasets</span></code></a>: Data Sets<a class="headerlink" href="#module-fatf.utils.data.datasets" title="Permalink to this headline">¶</a></h4>
<p>The <a class="reference internal" href="#module-fatf.utils.data.datasets" title="fatf.utils.data.datasets"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.datasets</span></code></a> module holds examples of data sets.</p>
<p>The iris data set is returned as a classic numpy array, whereas the health
records data set is a structured numpy array.</p>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.data.datasets.load_data.html#fatf.utils.data.datasets.load_data" title="fatf.utils.data.datasets.load_data"><code class="xref py py-obj docutils literal notranslate"><span class="pre">datasets.load_data</span></code></a></p></td>
<td><p>Loads a dataset from a file.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.utils.data.datasets.load_health_records.html#fatf.utils.data.datasets.load_health_records" title="fatf.utils.data.datasets.load_health_records"><code class="xref py py-obj docutils literal notranslate"><span class="pre">datasets.load_health_records</span></code></a></p></td>
<td><p>Loads in a fake health records dataset.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.data.datasets.load_iris.html#fatf.utils.data.datasets.load_iris" title="fatf.utils.data.datasets.load_iris"><code class="xref py py-obj docutils literal notranslate"><span class="pre">datasets.load_iris</span></code></a></p></td>
<td><p>Loads the IRIS dataset <a class="reference internal" href="generated/fatf.utils.data.datasets.load_iris.html#r47dce3bbc9de-fisher1936" id="id2"><span>[R47dce3bbc9de-FISHER1936]</span></a>.</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-fatf.utils.data.tools">
<span id="fatf-utils-data-tools-data-set-tools"></span><h4><a class="reference internal" href="#module-fatf.utils.data.tools" title="fatf.utils.data.tools"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.tools</span></code></a>: Data Set Tools<a class="headerlink" href="#module-fatf.utils.data.tools" title="Permalink to this headline">¶</a></h4>
<p>The <a class="reference internal" href="#module-fatf.utils.data.tools" title="fatf.utils.data.tools"><code class="xref py py-mod docutils literal notranslate"><span class="pre">fatf.utils.data.tools</span></code></a> module implements tools for data set handling.</p>
<table class="longtable docutils align-center">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.data.tools.group_by_column.html#fatf.utils.data.tools.group_by_column" title="fatf.utils.data.tools.group_by_column"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tools.group_by_column</span></code></a></p></td>
<td><p>Groups row indices of an array based on value grouping of a chosen column.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/fatf.utils.data.tools.apply_to_column_grouping.html#fatf.utils.data.tools.apply_to_column_grouping" title="fatf.utils.data.tools.apply_to_column_grouping"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tools.apply_to_column_grouping</span></code></a></p></td>
<td><p>Applies a function to the specified groups of labels and predictions.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/fatf.utils.data.tools.validate_indices_per_bin.html#fatf.utils.data.tools.validate_indices_per_bin" title="fatf.utils.data.tools.validate_indices_per_bin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tools.validate_indices_per_bin</span></code></a></p></td>