Cross-Validation and Hyperparameter Tuning in MLJ.jl
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An Introduction to Statistical Learning: With Applications in R, Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani, 2013 (Springer) - A widely-used textbook that covers fundamental concepts of cross-validation and hyperparameter tuning strategies.
MLJ.jl Documentation: Model Tuning, The MLJ.jl Contributors, 2024 (The Alan Turing Institute) - The official guide to hyperparameter tuning workflows and available strategies in MLJ.jl.
Random Search for Hyper-Parameter Optimization, James Bergstra, Yoshua Bengio, 2012Journal of Machine Learning Research, Vol. 13 (JMLR) - An influential paper that examines the effectiveness of random search compared to grid search for hyperparameter optimization.