Hyperparameter tuning for Machine Learning - Code Repository

Launched: May, 2021

Updated: September, 2024

Actively maintained.

Links

• Online Course

Table of Contents

1. Metrics

   1. Classification (accuracy, precision, recall, roc-auc, etc)
   2. Regression (MSE, RMSE, R2, etc)

2. Cross-Validation

   1. K-fold, LOOCV, LPOCV, Stratified CV
   2. Group CV and variants
   3. CV for time series
   4. Nested CV

3. Basic Search Algorithms

   1. Manual Search
   2. Grid Search
   3. Random Search

4. Bayesian Optimization

   1. with Gaussian Processes
   2. with Random Forests (SMAC) and GBMs
   3. with Parzen windows (Tree-structured Parzen Estimators or TPE)
   4. Simulated annealing

5. Multi-fidelity Optimization

   1. Successive Halving
   2. Hyperband

6. Python tools

   1. Scikit-learn
   2. Scikit-optimize
   3. Hyperopt
   4. Optuna

Links

• Online Course