Data Classification: Dimensionality Reduction Using Combined and Non-combined Multidimensional Projection Techniques

Abstract

Dimensionality Reduction is a commonly used method to reduce the number of dimensions of data. In this work, we verified its influence in classification process using combinations of projection techniques as dimensionality reduction algorithms. We also used Naïve Bayes and SMO as classifiers.