Some modelers prefer to partition the data into three data sets(training/validation/test) vs. the more typical two data sets(training/validation). A test set can be used during the finalmodeling step to measure the expected prediction error in practicegiven that it has been totally separated from themodeling/validation process. Do you think it is important topartition the data into three data sets (training/validation/test)or just two (training/validation)? Justify your opinion bydiscussing the pros and cons of each partitioning process.
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