A Novel Ensemble Method for Regression via Classification Problems
Halawani · Journal of Computer Science · 2011
Problem statement: Regression via Classification (RvC) is a method in which a regression problem is converted into a classification problem.A discretization process is used to covert continuous target value to classes.The discretized data can be used with classifiers as a classification problem.Approach: In this study, we use a discretization method, Extreme Randomized Discretization (ERD), in which bin boundaries are created randomly to create ensembles.Results: We show that the proposed ensemble method is useful for RvC problems.We show theoretically that the proposed ensembles for RvC perform better than RvC with the equal-width discretization method.We also show the superiority of the proposed ensemble method experimentally.Experimental results suggest that the proposed ensembles perform competitively to the method developed specifically for regression problems.Conclusion: As the proposed method is independent of the choice of the classifier, various classifiers can be used with the proposed method to solve the regression method.