Inductive-Analytical Learning based Stepwise Support Vector Machine (SVM) Model

Abstract- Support Vector Machines tend to perform better when dealing with multi-dimensions and continuous features. They work well with the data with high dimension also. This paper introduces the support vector machine (SVM) approach to the classification task in a step-wise manner to address mainly the high dimensional datasets. The task here is modeled as a supervised learning problem using SVM classifier in multiple steps. This approach has enabled to combine the inductive and analytical learning. Integrated learning systems, (i.e., systems that combine empirical and explanation-based learning or inductive and analytical learning) have the potential of overcoming the weakness of either method applied individually. This approach has been employed in proposing a step-wise SVM model in this paper