Chapter 6: Linear Regression Models - End-to-End Data Science with SAS [Book]

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Chapter 6: Linear Regression Models

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

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 ...

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