Working with Imbalanced Data sets

Theory : Imbalanced data sets, in the context of supervised classification problems, refer to the case when the class distribution is highly skewed or disproportionate. Since, general supervised learning algorithms assume them to be balanced, they perform accuracy maximisation. However, this in turn will propagate a model bias and be addressed to some extent, when…