A New Approach for Cluster Disjuncts Using Naive Bayes
Data mining is the process of discovering hidden knowledge from the existing databases. In real-time applications, most often data sources are of imbalanced nature. The traditional algorithms used for knowledge discovery are bottle necked due to wide range of data sources availability. Class imbalance is a one of the problem arises due to data source which provide unequal class i.e. examples of one class in a training data set vastly outnumber examples of the other class (es). Researchers have rigorously studied several techniques to alleviate the problem of class imbalance, including re-sampling algorithms, and feature selection approaches to this problem.