A Study on Regression Algorithm in Machine Learning


Authors : M.Ameerunnisa Begam, M.Guhapriya

Volume/Issue : Volume 5 - 2020, Issue 2 - February

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://bit.ly/2wfyyZb

Abstract : In this fast-moving world, millions of data and information exist and accessible to all. But from those collections, gathering exactly required data leads to predict accurate results. ML plays a vital role in converting the data into knowledge. Obliviously people are interacting with ML every day. From each and every interaction it constantly learns and improves the interaction. Regression is an important factor in ML. It determines the relationship among variables. This paper provides a study about regression algorithms such as Linear regression, Support Vector Machine, Random Forest along with their strengths and weaknesses.

Keywords : AI, ML, Regression, Support Vector Machine, Linear regression, Random Forest.

In this fast-moving world, millions of data and information exist and accessible to all. But from those collections, gathering exactly required data leads to predict accurate results. ML plays a vital role in converting the data into knowledge. Obliviously people are interacting with ML every day. From each and every interaction it constantly learns and improves the interaction. Regression is an important factor in ML. It determines the relationship among variables. This paper provides a study about regression algorithms such as Linear regression, Support Vector Machine, Random Forest along with their strengths and weaknesses.

Keywords : AI, ML, Regression, Support Vector Machine, Linear regression, Random Forest.

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