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Many real world data sets have an imbalanced distribution of the instances. Learning from such data sets results in the classifier being biased towards the majority class, thereby tending to misclassify the minority class samples. In this paper, we provide a technique, SkewBoost which classifies the minority instances correctly without compromising much on the correct classification of the majority...