Beginners Guide to Regression Analysis and Plot Interpretations
"The Road to Machine Learning starts with Regression. Are you ready?"
If you are aspiring to become a data scientist, regression is the first algorithm you need to learn to master. Not just to clear job interviews, but to solve real world problems.
Running a regression model is a no-brainer. A simple model <- y~x does the job. But optimizing this model for higher accuracy is a real challenge. Let's say your model gives adjusted R2 = 0.678; how will you improve it?
I've tried to make this guide comprehensive enough to help you get started building regression models. I've used R for practice purpose.
Table of Contents
1.What is Regression? How does it work?
2.What are the assumptions made in Regression?
3.How do I know if these assumptions are violated in my data?
4.How can I improve the accuracy of a Regression Model?
5.How can I access the fit of a Regression Model?
6. Practice Time - Solving a Regression Problem
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