January 2020
Intermediate to advanced
346 pages
9h 8m
English
Content preview from Hands-On Genetic Algorithms with Python
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Selecting the features for the Friedman-1 regression problem
The Friedman-1 regression problem, which was created by Friedman and Breiman, describes a single output value, y, which is a function of five input values, x0..x4, and randomly generated noise, according to the following formula:
The input variables, x0..x4, are independent, and uniformly distributed over the interval [0, 1]. The last component in the formula is the randomly generated noise. The noise is normally distributed and multiplied by the constant noise, which determines its level.
In Python, the scikit-learn (sklearn) library provides us with the make_friedman1() function, ...
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