Performance Analysis Of Different Classification Algorithms In Data Mining

Abstract

Data mining is a task carried out to extract valuable information from an immense amount of data. Data mining is generally used in every field to increase productivity by applying different algorithms on the data set. In the data mining field, numerous algorithms are developed to train different models so that they can be positively utilized in distinct sectors. Classification is one of the functions of data mining that posses’ different algorithms. In this paper, the work of various authors on classification algorithms is examined and the data set used by them is also evaluated. The paper presents a comparison table based on the evaluation made on different algorithms such asRandom Forest, logistic regression, and Naïve Bayes. The paper aims to identify the best algorithm based on accuracy.