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machine learning .py

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+# Advanced: Machine Learning Classifier Example
+from sklearn.datasets import load_iris
+from sklearn.model_selection import train_test_split
+from sklearn.tree import DecisionTreeClassifier
+from sklearn.metrics import accuracy_score
+
+# Load sample dataset
+data = load_iris()
+X, y = data.data, data.target
+
+# Split into train and test
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
+
+# Initialize and train the model
+model = DecisionTreeClassifier()
+model.fit(X_train, y_train)
+
+# Make predictions
+predictions = model.predict(X_test)
+
+# Evaluate
+accuracy = accuracy_score(y_test, predictions)
+print(f"✅ Model trained successfully!")
+print(f"Accuracy: {accuracy:.2f}")
+
+# Predict for a single sample
+sample = X_test[0].reshape(1, -1)
+predicted_class = model.predict(sample)[0]
+print(f"Example prediction → Class: {data.target_names[predicted_class]}")