Example set has no nominal label: using shuffled partition instead of stratified partition!
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Hi @User111113,
this warning applies to the attribute marked as label. This is the one you're predicting.
Stratified sampling is only available for nominal labels, for classification problems. If your label is numeric, then you're doing regression, which is fine.
Stratified sampling (e. g. in Split or Cross Validation) means keeping a similar ratio of the target classes in the test and the training sets. This is not available with regression, but that's OK.
If you set the operator that is now set to stratified sampling to shuffled, the warning should disappear.
Regards,
Balázs
this warning applies to the attribute marked as label. This is the one you're predicting.
Stratified sampling is only available for nominal labels, for classification problems. If your label is numeric, then you're doing regression, which is fine.
Stratified sampling (e. g. in Split or Cross Validation) means keeping a similar ratio of the target classes in the test and the training sets. This is not available with regression, but that's OK.
If you set the operator that is now set to stratified sampling to shuffled, the warning should disappear.
Regards,
Balázs
this warning applies to the attribute marked as label. This is the one you're predicting.
Stratified sampling is only available for nominal labels, for classification problems. If your label is numeric, then you're doing regression, which is fine.
Stratified sampling (e. g. in Split or Cross Validation) means keeping a similar ratio of the target classes in the test and the training sets. This is not available with regression, but that's OK.
If you set the operator that is now set to stratified sampling to shuffled, the warning should disappear.
Regards,
Balázs