Abstract
Data mining is also defined as the process of analyzing a quantity of data (usually a large amount) to find a logical relationship that summarizes the data in a new way that is understandable and useful to the owner of the data. This paper examines the various types of classification algorithms in Data Mining, their applications and categorically states the strengths and limitations of each type. The weaknesses found in each algorithm demonstrate how tasks cannot be performed well when only one type of algorithm is applied. For this reason, it is the view of the writer that further research needs to be carried out to explore the potential of combining several of these algorithms to solve machine learning problems. (C) 2020 The Authors. Published by IASE.