Open AccessLeast Square Regression for Prediction Problems in Machine Learning using R
Author(s) -
M Anila,
G. Pradeepini
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.12.17612
Subject(s) - ordinary least squares , regression , linear regression , regression analysis , regression diagnostic , popularity , statistics , computer science , cross sectional regression , econometrics , machine learning , artificial intelligence , polynomial regression , mathematics , psychology , social psychology
The most commonly used prediction technique is Ordinary Least Squares Regression (OLS Regression). It has been applied in many fields like statistics, finance, medicine, psychology and economics. Many people, specially Data Scientists using this technique know that it has not gone with enough training to apply it and should be checked why & when it can or can’t be applied.It’s not easy task to find or explain about why least square regression [1] is faced much criticism when trained and tried to apply it. In this paper, we mention firstly about fundamentals of linear regression and OLS regression along with that popularity of LS method, we present our analysis of difficulties & pitfalls that arise while OLS method is applied, finally some techniques for overcoming these problems.