Linear Regression in Machine Learning
Published: 2017
Author(s) Name: B. Ganapathy Subramaniam, T Rama Prabha |
Author(s) Affiliation: Research Scholar, Software Development, CEI India Private Limited, Chennai, Tamil Nadu, India.
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Abstract
Today, there are lot of research is about prediction which turns to be nothing but a concept of regression is all about as a part of Machine Learning. Machine Learning works heavily on natural language processing, computational biology, computer vision, robotics and other areas. Techniques of machine learning are very important to understand the data to apply the algorithms to answer questions based on the data. Regression describes the relationships between various variables. When looking at the words that describe the relationships in people, being independent or dependent, being simple or complex, being positive or negative and also being strong or weak. This turns out the all the adjectives being used are directly related to regression analysis. Regression analysis enhances the machine learning by reducing the errors of prediction and makes the estimated values closer to the actual values.
This paper briefly explains about the Machine learning and its most important technique called Linear regression with Gradient Descent.
Keywords: Gradient descent, Linear regression, Machine learning.
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