A methodological study and analysis of machine learning algorithms

Machine leaning algorithms have been used in vast area of research including stock market to medical informatics. Support vector machine (SVM), decision tree, random forest, K-nearest neighbors (KNN), naïve Bayes and multilayer perceptron (MLP) are widely used algorithms in different area of data classification. This paper provides theoretical and methodological prospective views based on different machine learning algorithms. For this latest literatures have been discussed with the aim and the scope. Based on the study the area applicability and the gaps have been identified for the future research.