Skip to content

Latest commit

 

History

History
60 lines (39 loc) · 1.71 KB

README.md

File metadata and controls

60 lines (39 loc) · 1.71 KB

PythonVersion License https://github.com/solegalli/hyperparameter-optimization/blob/master/LICENSE Sponsorship https://www.trainindata.com/

Hyperparameter tuning for Machine Learning - Code Repository

Launched: May, 2021

Updated: September, 2024

Actively maintained.

Links

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