October 2017
Beginner to intermediate
270 pages
7h
English
Content preview from Machine Learning for Developers
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Variance
As we saw in the first example, the mean isn't sufficient to describe non-homogeneous or very dispersed samples.
In order to add a unique value describing how dispersed the sample set's values are, we need to look at the concept of variance, which needs the mean of the sample set as a starting point, and then averages the distances of the samples from the provided mean. The greater the variance, the more scattered the sample set.
The canonical definition of variance is as follows:
Let's write the following sample code snippet to illustrate this concept, adopting the previously used libraries. For the sake of clarity, we are repeating ...
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