A Survey of Predictive Modelling under Imbalanced Distributions

Understand

Many real world data mining applications involve obtaining predictive models using data sets with strongly imbalanced distributions of the target variable.

• Frequently, the least common values of this target variable are associated with events that are highly relevant for end users (e.g.
• fraud detection, unusual returns on stock markets, anticipation of catastrophes, etc.).
• Moreover, the events may have different costs and benefits, which when associated with the rarity of some of them on the available training data creates serious problems to predictive modelling techniques.