What approaches are used to implement a model?

Asked on 14.12.2018 in All Questions.
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Before starting to implement a model, the data has been split into two parts: training and validation data will be 70% and test data 30%. To have a fair random division, Weka has a utility called “RemovePercentage” that allows removing some data, and through the flag “InsertSelection,” to have the rest of it. Test data is composed of 596 rows and training, and validation data are composed by 1391 rows. The first one is a...
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