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coursera-ml-007-exercises
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Predict

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neingeist 10 years ago
parent 31c4ac1967
commit c0b4d95f75
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ex2/predict.m
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@ -1,7 +1,7 @@
function p = predict(theta, X) function p = predict(theta, X)
%PREDICT Predict whether the label is 0 or 1 using learned logistic %PREDICT Predict whether the label is 0 or 1 using learned logistic
%regression parameters theta %regression parameters theta
% p = PREDICT(theta, X) computes the predictions for X using a % p = PREDICT(theta, X) computes the predictions for X using a
% threshold at 0.5 (i.e., if sigmoid(theta'*x) >= 0.5, predict 1) % threshold at 0.5 (i.e., if sigmoid(theta'*x) >= 0.5, predict 1)
m = size(X, 1); % Number of training examples m = size(X, 1); % Number of training examples
@ -11,10 +11,11 @@ p = zeros(m, 1);
% ====================== YOUR CODE HERE ====================== % ====================== YOUR CODE HERE ======================
% Instructions: Complete the following code to make predictions using % Instructions: Complete the following code to make predictions using
% your learned logistic regression parameters. % your learned logistic regression parameters.
% You should set p to a vector of 0's and 1's % You should set p to a vector of 0's and 1's
% %
p = sigmoid(X * theta) > 0.5;