neingeist/coursera-ml-007-exercises
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Add neural network prediction function

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neingeist 2014-10-23 23:36:15 +02:00
parent 3bf3d9fdc3
commit 073fbf0204
1 changed files with 14 additions and 5 deletions
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19
ex3/predict.m
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@ -7,12 +7,12 @@ function p = predict(Theta1, Theta2, X)
m = size(X, 1);
num_labels = size(Theta2, 1);
% You need to return the following variables correctly
% You need to return the following variables correctly
p = zeros(size(X, 1), 1);
% ====================== YOUR CODE HERE ======================
% Instructions: Complete the following code to make predictions using
% your learned neural network. You should set p to a
% your learned neural network. You should set p to a
% vector containing labels between 1 to num_labels.
%
% Hint: The max function might come in useful. In particular, the max
@ -21,13 +21,22 @@ p = zeros(size(X, 1), 1);
% can use max(A, [], 2) to obtain the max for each row.
%
% Theta1 has size 25x401
% Theta2 has size 10x26
a1 = [ones(m, 1) X];
% a1 has size mx401
a2_tmp = sigmoid(a1 * Theta1');
% a2_tmp has size m x 401 * 401 x 25 = m x 25
a2 = [ones(m, 1) a2_tmp];
% a2 has size m x 26
a3 = sigmoid(a2 * Theta2');
% a3 has size m x 26 * 26 x 10 = m x 10
% note: sigmoid not actually neded here (arg max(sigmoid(z)) = arg max(z))
[~, p] = max(a3, [], 2);
% =========================================================================