Chapter 3. Linear Regression
We've learned from previous chapters that regression problems involve predicting a numerical output. The simplest but most common type of regression is linear regression. In this chapter, we'll explore why linear regression is so commonly used, its limitations, and extensions, and then touch on polynomial regression, which you may consider when a linear relationship isn't a best fit for your circumstances.
Introduction to linear regression
In linear regression, the output variable is predicted by a linearly weighted combination of input features. Here is an example of a simple linear model:
The preceding model essentially ...
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