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Thread: Cross Validation in Weka

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  1. #1
    Join Date
    Mar 2012

    Default Cross Validation in Weka

    I've always studied that cross validation is performed like this:

    "In k-fold cross-validation, the original sample is randomly partitioned into k subsamples. Of the k subsamples, a single subsample is retained as the validation data for testing the model, and the remaining k − 1 subsamples are used as training data. The cross-validation process is then repeated k times (the folds), with each of the k subsamples used exactly once as the validation data. The k results from the folds then can be averaged (or otherwise combined) to produce a single estimation"

    So k models are built and the final one is averaged. In Weka guide is wrote that each model is always built using ALL the data set. So how cross validation in Weka works? Is the model built from all data and the "cross-validation" means that k fold are created then each fold is evaluated on it and the final output results is simply the averaged result from folds?
    Last edited by Lazza87; 04-12-2012 at 12:24 PM.

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