https://github.com/alessioborgi/mlpipeline_optimizationstudy

Exploration and optimization of a ML pipeline, delving into various techniques for enhancing different stages of ML workflows, including data preprocessing, feature engineering, model selection, and hyperparameter tuning.

catboost catboost-classifier data-imbalance gridsearchcv kernel-svm lightgbm lightgbm-classifier logistic-regression pca pca-analysis random-forest resource-complexity svm t-sne voting-ensemble xgboost xgboost-classifier

Last synced: 05 Apr 2025