Getting the message "warning: implicit conversion from real matrix to real scalar"

[brunoazev]

I have done an exercise to Coursera (predict handwritten digits), and
everything seems to be right but I'm getting this warning message and I
don't know why. Althought this message appears, the results are right as you
can see by the image below:

<http://octave.1599824.n4.nabble.com/file/n4659539/sshot-1.png> 

The code that results on that warning is:

function p = predict(Theta1, Theta2, X)
%PREDICT Predict the label of an input given a trained neural network
%   p = PREDICT(Theta1, Theta2, X) outputs the predicted label of X given
the
%   trained weights of a neural network (Theta1, Theta2)


m = size(X, 1);
num_labels = size(Theta2, 1);
p = zeros(size(X, 1), 1);

*a = sigmoid([ones(m,1) X] * Theta1');

[value,p] = max(sigmoid([ones(size(a),1) a] * Theta2'),[],2);*


________________________________

However, this works fine:

X = [ones(m, 1) X] ;

for c = 1:num_labels
        X2 = [ones(m, 1) (sigmoid(X * Theta1'))];
        predict(:,c) = sigmoid(X2 * Theta2(c,:)');
end

[predict, p] = max(predict, [], 2);


______________________________________

My doubt is why I'm getting the warning message in the first solution I
made.


Extra information:

X = 400 input layer units (excluding the extra bias unit which always
outputs +1). 
Theta1 has siz e 25 x 401.
Theta2 has size 10 x 26.




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