Selection of Classification and Regression Algorithms for Knowledge Discovery –A Review

In this era, it is a big challenge to classify the data and to extract the knowledge from the large-scale data according to the demand in different fields which is exhaustive in the digital world. Data being created by the internet, health … care, agriculture, financial, marketing, automotive industries, geo-information, and other sources at a very large- scale become big data. To discover the knowledge form the data, we need to use adaptive framework that uses optimal classification or regression machine learning algorithms. Our aim in this paper is to study, and analyze novel approaches of machine learning algorithms that are previously applied, analyzed by different researchers/ authors/ scholars for knowledge discovery. Our purpose is to review and select an efficient classification or regression algorithm so that we can introduce an adaptive framework in our future research. This review paper will be the milestone for new researchers/ scholars in the field of machine learning and knowledge discovery.