Moving course1 to course1 subdir.

machine_learning/course1/mlclass-ex5-008/mlclass-ex5/validationCurve.m

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+function [lambda_vec, error_train, error_val] = ...
+    validationCurve(X, y, Xval, yval)
+%VALIDATIONCURVE Generate the train and validation errors needed to
+%plot a validation curve that we can use to select lambda
+%   [lambda_vec, error_train, error_val] = ...
+%       VALIDATIONCURVE(X, y, Xval, yval) returns the train
+%       and validation errors (in error_train, error_val)
+%       for different values of lambda. You are given the training set (X,
+%       y) and validation set (Xval, yval).
+%
+
+% Selected values of lambda (you should not change this)
+lambda_vec = [0 0.001 0.003 0.01 0.03 0.1 0.3 1 3 10]';
+
+% You need to return these variables correctly.
+error_train = zeros(length(lambda_vec), 1);
+error_val = zeros(length(lambda_vec), 1);
+
+% ====================== YOUR CODE HERE ======================
+% Instructions: Fill in this function to return training errors in 
+%               error_train and the validation errors in error_val. The 
+%               vector lambda_vec contains the different lambda parameters 
+%               to use for each calculation of the errors, i.e, 
+%               error_train(i), and error_val(i) should give 
+%               you the errors obtained after training with 
+%               lambda = lambda_vec(i)
+%
+% Note: You can loop over lambda_vec with the following:
+%
+%       for i = 1:length(lambda_vec)
+%           lambda = lambda_vec(i);
+%           % Compute train / val errors when training linear 
+%           % regression with regularization parameter lambda
+%           % You should store the result in error_train(i)
+%           % and error_val(i)
+%           ....
+%           
+%       end
+%
+%
+m = size(X,1);
+mval = size(Xval,1);
+
+for i = 1:length(lambda_vec) 
+	theta = trainLinearReg(X, y, lambda_vec(i));
+	error_train(i) = sum( (X*theta - y) .^ 2 ) / (2*m);
+	error_val(i) = sum( (Xval*theta - yval) .^ 2 ) / (2*mval);
+end
+
+% =========================================================================
+
+end