Improving Classification Model's Performance Using Linear Discriminant Analysis on Linear Data

Abstract

Classification is a supervised learning technique for predicting the class of given data points. Before doing classification, it is essential to build a classification model using classification algorithms. There are several classification algorithms that can be used for prediction. Linear Discriminant Analysis (LDA) is used for reducing the dimensionality of datasets. This paper represents how LDA improves different classification model's performance.