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Cross-validation (actually, this is mentioned toward the end of the article). Basically, fit the the classifier with a subset of the data and test the predicti
by Bill_Dimm 12y ago
Cross-validation (actually, this is mentioned toward the end of the article). Basically, fit the the classifier with a subset of the data and test the predictions on the remainder. Predictions for out-of-sample data will be poor if you have overfitting.
http://en.wikipedia.org/wiki/Cross-validation_%28statistics%29 http://en.wikipedia.org/wiki/Cross-validation_%28statistics%...
- nraynaud 12y agoyeah, this one is quite intuitive, but it reduces the training sample size.
- Houshalter 12y agoOnce you find the optimal parameters, you can then train the model again on the entire dataset.