Add MLP activation function comparison script

machine_learning/mlp_activation_comparison.py

@@ -0,0 +1,31 @@
+import matplotlib.pyplot as plt
+from sklearn.neural_network import MLPClassifier
+from sklearn.datasets import make_moons
+from sklearn.model_selection import train_test_split
+from sklearn.metrics import accuracy_score
+
+X, y = make_moons(n_samples=500, noise=0.2, random_state=42)
+X_train, X_test, y_train, y_test = train_test_split(
+    X, y, test_size=0.3, random_state=42
+)
+
+activations = ["logistic", "tanh", "relu"]
+results = {}
+
+for act in activations:
+    clf = MLPClassifier(
+        hidden_layer_sizes=(10, 5),
+        activation=act,
+        solver="adam",
+        max_iter=1000,
+        random_state=42,
+    )
+    clf.fit(X_train, y_train)
+    y_pred = clf.predict(X_test)
+    acc = accuracy_score(y_test, y_pred)
+    results[act] = acc
+
+plt.bar(results.keys(), results.values())
+plt.title("Activation Function Comparison")
+plt.ylabel("Accuracy")
+plt.show()