Randomized Ensemble Approach with ID3 Algorithm For the Prediction datasets with Imbalance Problem

Abstract

Nowadays, it is significant to make accurate prediction model by handling imbalance problem. When the larger dataset has been used in the prediction model, that data should be classified into classes which gives ‘0’ and ‘1’ to indicate negative and positive results. While classifying this target value, the larger number of instances can reside in one class and the remaining lower number of instances can be stored in another class. Because of this unequal distribution of data, the machine can be biased and there is high possibility to give wrong predictions. An inaccurate Dataset leads to misprediction. Hence, the imbalanced prediction dataset has been taken. This paper gives a proper information on Randomized ensemble approach with ID3 classifier for the imbalanced prediction dataset.