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Add an extra
component with value 1 to each input vector.
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The bias
weight on this component is minus the
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threshold. Now we
can forget the threshold.
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Pick training
cases using any policy that ensures that
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every training
case will keep getting picked
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If
the output unit is correct, leave its weights alone.
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If
the output unit incorrectly outputs a zero, add the
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input
vector to the weight vector.
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If
the output unit incorrectly outputs a 1, subtract the
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input
vector from the weight vector.
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This is
guaranteed to find a suitable set of weights if any
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such
set exists.
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