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Training Systems Using Python Statistical Modeling

You're reading from   Training Systems Using Python Statistical Modeling Explore popular techniques for modeling your data in Python

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781838823733
Length 290 pages
Edition 1st Edition
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Author (1):
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Curtis Miller Curtis Miller
Author Profile Icon Curtis Miller
Curtis Miller
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Linear models

Let's start by discussing the basics of linear models. In this section, we will examine the objectives of regression, what a linear model is, and how to evaluate the quality of a fit. We will explore estimation with the help of OLS. Additionally, we will take a look at the OLS method of estimation in action by trying to predict the price of homes in Boston.

Classification and regression are both methods of prediction, but they each predict variables of different natures. For instance, classification predicts whether a data point belongs to one of a finite number of classes, such as whether a viewer clicks on an ad on a web page or not. On the other hand, regression predicts a value from a continuum, such as how much a customer will spend on a website. The following diagram demonstrates the difference between classification and regression:

Linear models are...

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