Data Mining with Weka (2.5: Cross-validation)

[@Appleiphones1]

Is Cross validation is used to avoid over-fitting?What is the difference between cross validation 2 and 10?

[@federicodimattia]

Sorry but I don't understand why weka run the algorithm an eleventh time. Thus, if the algorithm mentioned is the cross-validation algorithm, I don't understand how this can be applied to the whole dataset... if the cross-validation imply a divisione of the dataset (90-10) how can we apply it to the entire dataset? I'm a little bit confused...

[@patucao]

It suppose that you can get a better model if you use the entire dataset. The folds serve the purpose of evaluate the model, you don't need them to generate the actual model, what is done in the eleventh run.

[@Appleiphones1]

Is Cross validation is used to avoid over-fitting?What is the difference between cross validation 2 and 10?

[@martinl2603]

@@Appleiphones1 yes, it can be used to avoid overfivitting. 10-fold cross-valiation splits the data into 10 portions, while 2-fold cross-validation splits the data into two portions

[@abdallah.s1507]

i don't understand anything old man