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Python Machine Learning Cookbook by Prateek Joshi

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Building a linear regressor

Regression is the process of estimating the relationship between input data and the continuous-valued output data. This data is usually in the form of real numbers, and our goal is to estimate the underlying function that governs the mapping from the input to the output. Let's start with a very simple example. Consider the following mapping between input and output:

1 --> 2

3 --> 6

4.3 --> 8.6

7.1 --> 14.2

If I ask you to estimate the relationship between the inputs and the outputs, you can easily do this by analyzing the pattern. We can see that the output is twice the input value in each case, so the transformation would be as follows:

f(x) = 2x

This is a simple function, relating the input values with the output values. ...

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