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AI ML>Supervised Learning>Imbalanced And Cost-…

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Imbalanced And Cost-Sensitive Learning

31 terms

Data-Level Methods

10 terms

Random Over-Sampling
SMOTE
Borderline-SMOTE
ADASYN
Random Under-Sampling
NearMiss
Tomek Links
Edited Nearest Neighbors (ENN)
SMOTE-ENN
SMOTE-Tomek

Algorithm-Level Methods

7 terms

Threshold Moving
Ensemble Rebalancing
Balanced Random Forest
EasyEnsemble
BalanceCascade
Class-Balanced Loss
Cost-Sensitive Decision Trees

Cost-Sensitive Learning

7 terms

Class Weighting
Cost Matrix
Cost-Sensitive Loss
Weighted Loss Function
Misclassification Cost
Cost-Sensitive Decision Boundary
Bayes Risk Minimization

Evaluation For Imbalanced Data

7 terms

Balanced Accuracy
Geometric Mean Score
Precision-Recall Tradeoff
Macro Average
Micro Average
Weighted Average
Per-Class Metrics

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