2016-12-16 15:54:55 +00:00
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"""
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onehot('b', ['a', 'b', 'c', 'd']) => [false, true, false, false]
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onehot(Float32, 'c', ['a', 'b', 'c', 'd']) => [0., 0., 1., 0.]
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Produce a one-hot-encoded version of an item, given a list of possible values
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for the item.
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"""
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2016-10-29 22:36:39 +00:00
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onehot(T::Type, label, labels) = T[i == label for i in labels]
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onehot(label, labels) = onehot(Int, label, labels)
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2016-12-16 15:54:55 +00:00
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"""
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onecold([0.0, 1.0, 0.0, ...],
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['a', 'b', 'c', ...]) => 'b'
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The inverse of `onehot`; takes an output prediction vector and a list of
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possible values, and produces the appropriate value.
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"""
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2017-04-19 13:23:48 +00:00
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onecold(y::AbstractVector, labels = 1:length(y)) =
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labels[findfirst(y, maximum(y))]
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onecold(y::AbstractMatrix, l...) =
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squeeze(mapslices(y -> onecold(y, l...), y, 2), 2)
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2016-10-29 22:36:39 +00:00
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2017-06-06 17:03:14 +00:00
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chunk(xs, n) = Base.Iterators.partition(xs, length(xs)÷n)
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