| from src.protify.probes.lazy_predict import LazyClassifier, LazyRegressor | |
| import numpy as np | |
| import argparse | |
| # Example usage: | |
| #python -m src.protify.testing_suite.test_lazy_predict --verbose 1 | |
| #python -m src.protify.testing_suite.test_lazy_predict --verbose 0 | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--verbose", type=int, default=0, help="0=summary, 1=full table") | |
| args = parser.parse_args() | |
| # Small synthetic data | |
| X = np.random.rand(100, 10) | |
| y = np.random.randint(0, 2, 100) | |
| clf = LazyClassifier(classifiers="all", verbose=args.verbose) | |
| clf_scores = clf.fit(X[:80], X[80:], y[:80], y[80:]) | |
| # Test regressor with continuous target | |
| y_reg = np.random.rand(100) | |
| rg = LazyRegressor(regressors="all", verbose=args.verbose) | |
| rg_scores = rg.fit(X[:80], X[80:], y_reg[:80], y_reg[80:]) |