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Fitting
hyperplanes as
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separators is
mathematically
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easy.
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The
mathematics is linear.
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By replacing the
raw input
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variables with a
much larger
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set of features
we get a nice
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property:
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A
planar separator in the
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high-dimensional
space of
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feature
vectors is a curved
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separator
in the low
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dimensional
space of the
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raw
input variables.
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