Performance of Machine Learning Algorithms in Distributed Environment: A Study

Abstract

In present scenario, to extract and study meaningful data from vast volumes of data using modern tools and techniques are necessary for making decisions. For analysing large volumes of data using a Distributed Environment with big data is efficient because it gives a solution to manage contents in the distributed system. To implement and analyse the data, three different sizes of datasets from various fields are considered. Then data is analysed in both Distributed Environment and Standalone Environment because it will provide which Environment is scalable and also to know the performance and improvement of data analysis. In this process for predicting and analysing the different sizes of data various algorithms in machine learning are applied to datasets with extensive data framework. Therefore, all applied algorithms in both environments are compared with their accuracies, precision, and re-call with time to know the best algorithm and environment.