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#!/usr/bin/env python3
"""
Basic example demonstrating AutoML Lite usage.
"""
import pandas as pd
import numpy as np
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from automl_lite import AutoMLite
def main():
"""Run a basic AutoML Lite example."""
print("🤖 AutoML Lite - Basic Example")
print("=" * 50)
# Generate sample data
print("📊 Generating sample classification data...")
X, y = make_classification(
n_samples=1000,
n_features=10,
n_informative=5,
n_redundant=2,
n_clusters_per_class=1,
random_state=42
)
# Convert to DataFrame
feature_names = [f'feature_{i}' for i in range(X.shape[1])]
X_df = pd.DataFrame(X, columns=pd.Index(feature_names))
y_series = pd.Series(y, name='target')
print(f"Dataset shape: {X_df.shape}")
print(f"Target distribution:\n{y_series.value_counts()}")
# Split data
X_train, X_test, y_train, y_test = train_test_split(
X_df, y_series, test_size=0.2, random_state=42, stratify=y_series
)
print(f"\nTraining set: {X_train.shape}")
print(f"Test set: {X_test.shape}")
# Initialize AutoML Lite
print("\n🚀 Initializing AutoML Lite...")
automl = AutoMLite(
time_budget=120, # 2 minutes
max_models=3, # Try 3 models
cv_folds=3, # 3-fold CV
random_state=42,
verbose=True
)
# Train the model
print("\n🎯 Training AutoML model...")
automl.fit(X_train, y_train)
# Results
print(f"\n✅ Training completed!")
print(f"Best model: {automl.best_model_name}")
print(f"Best CV score: {automl.best_score:.4f}")
# Make predictions
print("\n🔮 Making predictions...")
y_pred = automl.predict(X_test)
test_score = automl.score(X_test, y_test)
print(f"Test accuracy: {test_score:.4f}")
# Show leaderboard
print("\n🏆 Model Leaderboard:")
leaderboard = automl.get_leaderboard()
print(leaderboard)
# Show feature importance
print("\n🎯 Feature Importance (Top 5):")
feature_importance = automl.get_feature_importance()
print(feature_importance.head())
# Save model
print("\n💾 Saving model...")
automl.save_model("example_model.pkl")
# Generate report
print("\n📋 Generating report...")
automl.generate_report("example_report.html")
print("\n🎉 Example completed successfully!")
print("📁 Files created:")
print(" - example_model.pkl (saved model)")
print(" - example_report.html (comprehensive report)")
return 0
if __name__ == "__main__":
exit(main()) |