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Combined labels
Contributor II
Dear All
I would like to run attribute weighting models on a dataset with 5 features as labels. I want to combine the features (not running the model for each label every time, I mean I don't want to use the loop label operator). I want the see the weight for each feature based on 5 label combinations.
Any suggestion?
Many thanks.
Mansour
I would like to run attribute weighting models on a dataset with 5 features as labels. I want to combine the features (not running the model for each label every time, I mean I don't want to use the loop label operator). I want the see the weight for each feature based on 5 label combinations.
Any suggestion?
Many thanks.
Mansour
0
Answers
Are you able to provide a little more detail or sample of the data? Are these numeric or categorical labels?
Jeff
Thanks for your reply. They are both numerical and categorical and in some instances a mixture of both.
Best wishes.
Mansour
I think for the purposes of seeing the weights across all labels, one approach would be to bin the numeric labels as necessary, and simply concatenate your labels. You end up with a high number of unique classes, but it may serve your purposes, particularly if you have enough data to support it. If you are able to provide any more information about the data, like a sample, and the size, and any process that you might have, then we might be able to get some more responses.
Jeff
Many thanks. To make it simple, I converted all numeric label variables to Quartiled (so there are four classes in each variable, Q1 to Q4). Now how can I compute weights for each regular feature based on five categorical target features (not individually).
Best wishes.
Mansour