Comprehensive Review On Supervised Machine Learning Algorithms

Abstract

Machine learning is an area of computer science in which the computer predicts the next task to perform by analyzing the data provided to it. The data accessed by the computer can be in the form of digitized training sets or via interaction with the environment. The algorithms of machine learning are constructed in such a way as to learn and make predictions from the data unlike the static programming algorithms that need explicit human instruction. There have been different supervised and unsupervised techniques proposed in order to solve problems, such as, Rule-based techniques, Logic-based techniques, Instance-based techniques, stochastic techniques. The primary objective of our paper is to provide a general comparison among various state-of-the-art supervised machine learning algorithms.