Skip to Main Content
End-to-End Data Science with SAS
book

End-to-End Data Science with SAS

by James Gearheart
June 2020
Beginner to intermediate content levelBeginner to intermediate
380 pages
11h 32m
English
SAS Institute
Content preview from End-to-End Data Science with SAS

Chapter 6: Linear Regression Models

Overview

Regression Structure

Gradient Descent

Linear Regression Assumptions

Linear Relationship

Multivariate Normality

Multicollinearity

Autocorrelation

Homoscedasticity

Linear Regression

Analyze the Target Variable

Analyze the Predictor Variables

Simple Linear Regression

Multiple Linear Regression

Multiple Linear Regression Equation

Parsimonious Multiple Regression Model

Regularization Models

Ridge Regression

Lasso Regression

Chapter Review

Overview

In the previous chapter, we reviewed the ETL process and all the various data transformations required to prepare a raw data set a modeling data set. This time-consuming process was necessary to ensure that the data is optimized for modeling purposes. Raw data ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Tree-Based Machine Learning Methods in SAS Viya

Tree-Based Machine Learning Methods in SAS Viya

Dr. Sharad Saxena
Big Data Analytics with SAS

Big Data Analytics with SAS

David Pope, Subhashini S Tripathi

Publisher Resources

ISBN: 9781642958065