September 2017
Beginner to intermediate
270 pages
5h 53m
English
Content preview from Neural Networks with R
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Linear separation
When a set of output values can be split by a straight line, the output values are said to be linearly separable. Geometrically, this condition describes the situation in which there is a hyperplane that separates, in the vector space of inputs, those that require positive output from those that require a negative output, as shown in the following figure:
Here, one side of the separator are those predicted to belong to one class whilst those on the other side are predicted to belong to a different class. The decision rule of the Boolean neuron corresponds to the breakdown of the input features space, operated by a hyperplane. ...
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