吴恩达的机器学习编程作业9：predict 神经网络预测结果

最新推荐文章于 2022-10-29 11:55:24 发布

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最新推荐文章于 2022-10-29 11:55:24 发布

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分类专栏：机器学习 from 吴恩达

本文链接：https://blog.youkuaiyun.com/melon__/article/details/80824229

这段代码展示了如何利用训练好的神经网络权重Theta1和Theta2进行预测。通过添加偏置项，计算隐藏层和输出层的激活值，然后应用sigmoid函数，最终使用max函数找出最大概率对应的类别标签。

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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];
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