PyData SF 2016 Ajinkya More | Resampling techniques and other strategies for handling highly unbalanced datasets in classification
Many real world machine learning problems need to deal with imbalanced class distribution i.e. when one class has significantly higher/lower representation than the other classes. Often performance on the minority class is more crucial, e.g. fraud detection, product classification, medical diagnosis, etc. In this talk I will discuss several techniques to handle class imbalance in classification.