K-fold Cross Validation Performance

Hello All, I am a newbie in Validating models, I am currently trying to make use of the MATLAB K-fold validation to assess the performance of my polynomial model that predicts house prices. I have 243 samples, i divided them into 10 groups, i then used 'for loop' to test 9 groups against 1 group (repeated X 10) My problem is storing the error rate (performance) for the 10 times i am making the prediction. How do i do that please? I tried making use of 'classperf' but i am getting the following error, Please see my code below;

Data set sample:

DateX: 10,20,30,40 ... PriceY: 200,250,300,400 ...

--------Code (MATLAB)-------

K = 10;

cvFolds = crossvalind('Kfold',DateX,K); %10-folds

cp = classperf(DateX); %To store (performance)

for i = 1:K

testIDx = (cvFolds == i);

trainIDx = ~testIDx;

model1 = polyfit(DateX(trainIDx),PriceY(trainIDx),2);

prediction1=model1(1)*DateX(testIDx).^2+model1(2)*DateX(testIDx)+model1(3);

cp = classperf(cp,prediction1,testIDx);

end

My Error Message;

Error using classperf (line 230) When the class labels of the CP object are numeric, the output of the classifier must be all non-negative integers or NaN's.

Is there any suggestions please on how i can store the performance of my model AND i would apperciate examples of other methods In MATLAB that i can apply to make predictions and validate performance (Neural networks, Classification e.t.c.)?? THANK YOU!

Answer 1

[Greg Heath]

I do not have the functions crossvalind and classperf.

Although I do have crossval and cvpartition, I favor my own code used in the following NEWSGROUP posts:

 http://www.mathworks.com/matlabcentral/newsreader/view_thread/326830#898048

 http://www.mathworks.com/matlabcentral/newsreader/view_thread/331830#911882

Hope this helps.

Thank you for formally accepting my answer

Greg