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Xvalidation
hi,
i am a rapid-i novice.
i want to train the model on a specific set of data and then test on another specific set. from what i can see (so far), there is a round about way of doing this by using:
Xvalidation and selelecting sampling_type = "linear sampling" and number_of_validations = 2
although this requires that both training and testing data sets have the same number of elements and are in a particular order.
is there a more general / sensible way of doing this? in particular, can i base the sampling on one of the data attributes?
many thanks, evgeny.
i am a rapid-i novice.
i want to train the model on a specific set of data and then test on another specific set. from what i can see (so far), there is a round about way of doing this by using:
Xvalidation and selelecting sampling_type = "linear sampling" and number_of_validations = 2
although this requires that both training and testing data sets have the same number of elements and are in a particular order.
is there a more general / sensible way of doing this? in particular, can i base the sampling on one of the data attributes?
many thanks, evgeny.
0
Answers
Welcome to the world of countless combinations! Sure, linear sampling in a validation wrapper would work, with the limitations you spot, but you can always go freestyle....
1. Filter your examples by attribute value to make a training set.
2. Add a learner to make a model, but do not keep the training examples.
3. Load your test set and apply the model.
4. Have a beer, and examine the results.
Actually the XVal operators just bundle this up so you can test repeatedly, but don't stop for the beer ( but you can always insert a break for that ;D ).
Good luck!