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machine_learning/mlp_activation_comparison.py

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# Define classifiers with different activation functions
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classifiers = {
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"relu": MLPClassifier(hidden_layer_sizes=(10, 10), activation="relu", max_iter=2000, random_state=42),
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"tanh": MLPClassifier(hidden_layer_sizes=(10, 10), activation="tanh", max_iter=2000, random_state=42),
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"logistic": MLPClassifier(hidden_layer_sizes=(10, 10), activation="logistic", max_iter=2000, random_state=42),
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"relu": MLPClassifier(
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hidden_layer_sizes=(10, 10), activation="relu", max_iter=2000, random_state=42
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),
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"tanh": MLPClassifier(
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hidden_layer_sizes=(10, 10), activation="tanh", max_iter=2000, random_state=42
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),
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"logistic": MLPClassifier(
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hidden_layer_sizes=(10, 10),
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activation="logistic",
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max_iter=2000,
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random_state=42,
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),
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}
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# Plot decision boundaries

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