A Perspective Overview on Machine Learning Algorithms

Abstract

The latest innovations of technology now a days, avails the massive collection of information from various sources which leads to solve many real life challenges. The key challenge is to design the right model by handling the massive data. From past researches, there were so many misinterpretations made due to wrong choice of models. The lack of skill lies in handling the conservative data, designing the effective reasoning capabilities and handling missing data has triggered an increase in the number of studies using non-conventional methods like machine learning techniques. The study of machine learning which is a subset of Artificial Intelligence focusses on efficient and accurate prediction process by automating the knowledge engineering process avoiding the human intervention. In this research, the focus is made on the popularly used machine learning algorithms like K-Nearest Neighbors (KNN), Naive Bayes (NB), Support Vector Machine (SVM) and Decision Trees (DT) along with their suitability, advantages and disadvantages with performance accuracy.