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1 parent c235a71 commit 25571d5Copy full SHA for 25571d5
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machine_learning/tsne.py
@@ -5,7 +5,7 @@
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t-SNE is a nonlinear dimensionality reduction algorithm for visualizing
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high-dimensional data in a low-dimensional space (2D or 3D).
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-It computes pairwise similarities in both spaces and minimizes the
+It computes pairwise similarities in both spaces and minimizes the
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Kullback-Leibler divergence using gradient descent.
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References:
@@ -37,9 +37,7 @@ def collect_dataset() -> tuple[np.ndarray, np.ndarray]:
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return np.array(data.data), np.array(data.target)
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-def compute_pairwise_affinities(
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- data_x: np.ndarray, sigma: float = 1.0
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-) -> np.ndarray:
+def compute_pairwise_affinities(data_x: np.ndarray, sigma: float = 1.0) -> np.ndarray:
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"""
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Compute high-dimensional affinities (P matrix) using Gaussian kernel.
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