Imbalanced

Helpful examples for imbalanced classification, e.g. where the number of instances for each class in the training set are not equal.

It may also sometimes be called unbalanced classification.

Examples	Tags
XGBoost "scale_pos_weight" Parameter Unused For Regression	Parameters Imbalanced Regression
XGBoost "scale_pos_weight" vs "sample_weight" for Imbalanced Classification	Train Parameters Imbalanced
XGBoost Configure "class_weight" Parameter for Imbalanced Classification	Train Parameters Imbalanced
XGBoost Configure "max_delta_step" Parameter for Imbalanced Classification	Train Parameters Imbalanced
XGBoost Configure "sample_weight" Parameter for Imbalanced Classification	Train Parameters Imbalanced
XGBoost Configure "scale_pos_weight" Parameter	Train Parameters Imbalanced
XGBoost Configure fit() "sample_weight" Parameter	Train Imbalanced
XGBoost Evaluate Model using Stratified k-Fold Cross-Validation	Evaluate Imbalanced Classification
XGBoost for Imbalanced Classification	Train Classification Imbalanced
XGBoost for Imbalanced Classification with SMOTE	Train Data Imbalanced
XGBoost Imbalanced Multi-class Classification set "sample_weight" using compute_sample_weight()	Train Imbalanced
XGBoost Multi-Class Imbalanced Classification	Train Imbalanced
XGBoost Threshold Moving for Imbalanced Classification	Classification Imbalanced
XGBoost Tune "max_delta_step" Parameter for Imbalanced Classification	Tune Imbalanced
XGBoost Tune "scale_pos_weight" Parameter	Tune Imbalanced