Machine Learning - Data Mining, Preparatory PhaseLeave a comment

Imbalanced Learning: sampling techniques

May 24, 2020April 10, 2022 Tung.M.Phung

Various types of sampling techniques for imbalanced datasets are discussed in depth with examples and analysis. Get yourself familiar with over-/under-sampling, SMOTE, ADA-SYN, sampling with cleaning, boosting, clustering, and more. Continue reading Imbalanced Learning: sampling techniques

Classification Models, Machine Learning - Data Mining, Regression ModelsLeave a comment

Ensemble: Bagging, Random Forest, Boosting and Stacking

May 4, 2020July 31, 2020 Tung.M.Phung

An ensemble of trees (in the form of bagging, random forest, or boosting) is usually preferred over one decision tree alone. Continue reading Ensemble: Bagging, Random Forest, Boosting and Stacking

Tung M Phung's Blog

Tag: ensemble

Imbalanced Learning: sampling techniques

Ensemble: Bagging, Random Forest, Boosting and Stacking