Best Resources for Imbalanced Classification
Last Updated on January 14, 2020 Classification is a predictive modeling problem that involves predicting a class label for a given example. It is generally assumed that the distribution of examples in the training dataset is even across all of the classes. In practice, this is rarely the case. Those classification predictive models where the distribution of examples across class labels is not equal (e.g. are skewed) are called “imbalanced classification.” Typically, a slight imbalance is not a problem and […]
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