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time series cross validation in svm

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mono on 7 Aug 2019
I am trying to write a kernel based regression model (svm or gaussian process) to predict time series data. I note that fitrsvm has cross validation input arguement that random shuffs the set and generate both training and validation sets. BUT, I am working on a time series data that the built in cross validation or kfold methods is not a good choice due to the data sequencial property.
Would be appreciated if anyone can give a tip or two to tackle the task while still using fitrgp or fitrsvm functions...


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