Class Imbalance Strategies
Class Imbalance Strategies groups the core ideas a learner needs at the 7 · modelling & training stage. Work through the lessons in order when new to the area, or use them independently as a reference when implementing an analysis.
Learn the mechanism one decision at a time
Work through the lessons in order if the topic is new. If you already know the basics, open the specific leaf lesson that matches the operation, diagnostic or failure mode you need.
1Definition→
2Mechanism→
3Example→
4Diagnostic→
5Decision
Diagnose imbalanceDiagnose imbalance is a practical concept within Class Imbalance Strategies. It helps turn the broader workflow stage “7 · Modelling & Training” into an explicit analytical decision that can be explained, implemented and checked. The concept should be understood in terms of purpose, mechanism, assumptions, evidence and downstream consequences.
02Stratified evaluationStratified evaluation is a practical concept within Class Imbalance Strategies. It helps turn the broader workflow stage “7 · Modelling & Training” into an explicit analytical decision that can be explained, implemented and checked. The concept should be understood in terms of purpose, mechanism, assumptions, evidence and downstream consequences.
03Class weightsClass weights is a practical concept within Class Imbalance Strategies. It helps turn the broader workflow stage “7 · Modelling & Training” into an explicit analytical decision that can be explained, implemented and checked. The concept should be understood in terms of purpose, mechanism, assumptions, evidence and downstream consequences.
04Random under-samplingRandom under-sampling is part of study design: it determines which units enter the dataset and therefore which population the analysis can legitimately represent. A good sampling decision balances representativeness, cost, variance and the practical mechanism by which observations become available.
05Random over-samplingRandom over-sampling is part of study design: it determines which units enter the dataset and therefore which population the analysis can legitimately represent. A good sampling decision balances representativeness, cost, variance and the practical mechanism by which observations become available.
06SMOTE intuitionSMOTE intuition is a practical concept within Class Imbalance Strategies. It helps turn the broader workflow stage “7 · Modelling & Training” into an explicit analytical decision that can be explained, implemented and checked. The concept should be understood in terms of purpose, mechanism, assumptions, evidence and downstream consequences.
07Threshold movingThreshold moving is a practical concept within Class Imbalance Strategies. It helps turn the broader workflow stage “7 · Modelling & Training” into an explicit analytical decision that can be explained, implemented and checked. The concept should be understood in terms of purpose, mechanism, assumptions, evidence and downstream consequences.
08Precision-recall focusPrecision-recall focus is an evaluation quantity that compresses a particular aspect of predictive behaviour into a number. Its usefulness depends on whether that aspect matches the real decision cost, class prevalence and intended model output.