我正在做教授。 Ng的Coursera ML课程。 这是问题所在。 我正在尝试实现以下模型:
,这是我的代码:
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)
% Useful values
m = size(X, 1);
num_labels = size(Theta2, 1);
% 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
% vector containing labels between 1 to num_labels.
%
% Hint: The max function might come in useful. In particular, the max
% function can also return the index of the max element, for more
% information see 'help max'. If your examples are in rows, then, you
% can use max(A, [], 2) to obtain the max for each row.
%
X = [ones(m,1) X];%X:5000*401
z2 = Theta1*X';%z2: 25*5000
z2_n = size(z2,2);%
a2 = [sigmoid(z2); ones(1,z2_n)];%theta1_x: 26*5000
z3 = Theta2*a2;%z3: 10*5000
a3 = sigmoid(z3);
[a, p] = max(a3, [], 1);
% =========================================================================
end
但是我得到了很多错误的预测,实现的哪一部分是错误的? 感谢任何建议。
答案 0 :(得分:1)
问题始于z2
z2 = X * Theta1';
a2 = [ones(size(z2, 1), 1) sigmoid(z2)];
z3 = a2 * Theta2';
a3 = sigmoid(z3);
[pmax, p] = max(a3, [], 2)