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45 lines
1.4 KiB
Matlab
45 lines
1.4 KiB
Matlab
function p = predict(Theta1, Theta2, X)
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%PREDICT Predict the label of an input given a trained neural network
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% p = PREDICT(Theta1, Theta2, X) outputs the predicted label of X given the
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% trained weights of a neural network (Theta1, Theta2)
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% Useful values
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m = size(X, 1);
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num_labels = size(Theta2, 1);
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% You need to return the following variables correctly
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p = zeros(size(X, 1), 1);
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% ====================== YOUR CODE HERE ======================
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% Instructions: Complete the following code to make predictions using
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% your learned neural network. You should set p to a
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% vector containing labels between 1 to num_labels.
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%
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% Hint: The max function might come in useful. In particular, the max
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% function can also return the index of the max element, for more
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% information see 'help max'. If your examples are in rows, then, you
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% can use max(A, [], 2) to obtain the max for each row.
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%
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% Theta1 has size 25x401
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% Theta2 has size 10x26
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a1 = [ones(m, 1) X];
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% a1 has size mx401
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a2_tmp = sigmoid(a1 * Theta1');
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% a2_tmp has size m x 401 * 401 x 25 = m x 25
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a2 = [ones(m, 1) a2_tmp];
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% a2 has size m x 26
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a3 = sigmoid(a2 * Theta2');
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% a3 has size m x 26 * 26 x 10 = m x 10
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% note: sigmoid not actually neded here (arg max(sigmoid(z)) = arg max(z))
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[~, p] = max(a3, [], 2);
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% =========================================================================
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end
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