MATLAB: Crossvalidation of liinear models

linear model

Hi, does anyone knows if there is a function to crossvalidated my linear model? i can only find it for descision trees unfortunately.. Thank you!

Best Answer

help crossval, doc crossval

help cvpartition, doc cvpartition

Hope this helps

Thank you for formally accepting my answer

Greg

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MATLAB: Leave-One-Out with ROC

Here is an example for cross-validating a discriminant model: http://www.mathworks.com/help/stats/discriminant-analysis.html#bs2r8ue. Here is a description of the crossval method: http://www.mathworks.com/help/stats/classificationdiscriminant.crossval.html. You can just replace 'kfold',5 with 'leaveout','on' in that example.

MATLAB: Doubts about cross-validation

I am assuming that you want to have some clarification regarding the cross-validation syntax in KNN and SVM

KNN Classifier

mdlknn = fitcknn(X,labels, 'NumNeighbors', ... 
                   k, 'Distance',@distKNN, 'Leaveout','on',... 
                    'HyperparameterOptimizationOptions','UseParallel'); 
 
mdlknnNoCrossVal = fitcknn(X,labels, 'NumNeighbors', ... 
                   k, 'Distance',@distKNN, 'HyperparameterOptimizationOptions','UseParallel'); 
mdlknn = crossval(mdlknnNoCrossVal, 'leaveout','on')

These two syntaxes may be equivalent for the creation of a cross-validated KNN model. “mdlknn" is a "ClassificationPartitionModel" classifier. "mdlknnNoCrossVal” creates a "ClassificationKNN" classifier which is cross validated using the “crossval” function.

ECOC classifier

In the case of ECOC classifier you may use the “templateKNN” as the learner. It provides the feature to customize the distance metric using the ‘Distance’ argument. The distance metric can be passed as a function handle like that of the KNN classifier syntax.

And the two syntaxes are valid for the process of cross validation in the case of ECOC also.

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MATLAB: Leave-One-Out with ROC

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