Scikit-learn Debugging Guide

This guide provides a systematic approach to debugging Scikit-learn machine learning code. Follow these phases to identify and resolve issues efficiently.

Common Error Patterns

1. ValueError: Shapes Not Aligned

# Error: ValueError: shapes (100,5) and (4,) not aligned
# Cause: Feature count mismatch between train and test data

# Debug steps:
print(f"X_train shape: {X_train.shape}")
print(f"X_test shape: {X_test.shape}")
print(f"Feature names train: {X_train.columns.tolist() if hasattr(X_train, 'columns') else 'N/A'}")
print(f"Feature names test: {X_test.columns.tolist() if hasattr(X_test, 'columns') else 'N/A'}")

# Common fixes:
# 1. Ensure same preprocessing on train and test