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2 parents 1d288cf + e7f0397 commit 32417e5Copy full SHA for 32417e5
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doc/logreg.txt
@@ -68,8 +68,11 @@ The code to do this in Theano is the following:
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b = theano.shared(numpy.zeros((10,)), name='b')
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W = theano.shared(numpy.zeros((784, 10)), name='W')
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- # symbolic expression for computing the vector of
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- # class-membership probabilities
+ # symbolic expression for computing the matrix of class-membership probabilities
+ # Where:
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+ # W is a matrix where column-k represent the separation hyper plain for class-k
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+ # x is a matrix where row-j represents input training sample-j
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+ # b is a vector where element-k represent the free parameter of hyper plain-k
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p_y_given_x = T.nnet.softmax(T.dot(x, W) + b)
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# compiled Theano function that returns the vector of class-membership
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