International Journal of Computer Informatics & Technological Engineering (IJCITE)
In last few years, in order to classify data there are various changes and evolution are evolved. Due to its unbounded size and imbalanced nature of data, classification of data has become more difficult. Classification of imbalanced dataset is an important mission of Knowledge Discovery in Databases (KDDs) and data mining. Imbalanced dataset occurs where the number of samples of one class is much higher than that of other classes. In machine learning, the class imbalance problem has become a greatest issue and found in several applications such as remote-sensing, detecting fraud, detecting network intrusions, biomedical engineering, text classification and data stream classification.