Cross-Validation

Summary

Splitting data into multiple folds and rotating which fold is used for validation — a more robust way to estimate how a model will generalize than a single train/test split.

How to Learn This

1Implement K-fold cross-validation with scikit-learn's `cross_val_score`.
2Learn stratified K-fold for classification and time-series-aware splitting for temporal data.
3Use cross-validation results to compare two candidate models fairly.

Train/Test Split

House Price Prediction

More topics in Machine Learning Fundamentals

Supervised vs Unsupervised Learning Linear Regression Logistic Regression Decision Trees Random Forests K-Nearest Neighbors K-Means Clustering Support Vector Machines Naive Bayes scikit-learn Basics Train/Test Split

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