February 2019
Beginner to intermediate
382 pages
10h 1m
English
The hyperplanes we have found up till now are linear, for instance, a line in a two-dimensional feature space, or a surface in a three-dimensional one. However, in the following example, we are not able to find any linear hyperplane that can separate two classes:

Intuitively, we observe that data points from one class are closer to the origin than those from another class. The distance to the origin provides distinguishable information. So we add a new feature,
, and transform the original two-dimensional ...
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