Evaluating Efficacy of Classification Algorithms on Personality Prediction Dataset

Abstract

Classification is a term that denotes to the process of labelling given input data pieces into predefined groups in machine learning. There are numerous classification algorithms focused on bayes, trees, functions, or laws that are commonly used. For a long time, the competence of these algorithmic approaches has become a big concern, attracting the attention of a sizable study group. The aim of this article is to examine the efficacy of various classification algorithms. There are several machine learning algorithms for classifying rules and performing various functions. This article compares classification algorithms used to identify and forecast personality using the HEXACO Model dataset and backs it up with implementation performance.