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I have a data set where there the target column as values between 1-15. Now I need to predict that based on the features. the feature values are have unqiue IDs. but the target column is the same value range. one row could looks like

1,0.5,2.3,1.23,5 where first entry is the id and last entry is the target. In that why I have total 500 uniq IDs which has different feature values but same target range.

Now I would like to ask should I take the ID in the traning process ? or take features ? Or what would be the best approch for this classification ?

so one

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I believe all id's are unique(no repetitions/duplicates). You can delete this variable and proceed for analysis. The variables like this(ids) and the variables which have the same values (zero variance) are not at all able to draw patterns to predict the target variable. You can delete these type of variables without a doubt.

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