Wrong target! about pmlb HOT 3 CLOSED

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We need discuss about whether we should keep this train/test selector into the dataset or not. If we keep the selector then the metafeature need annotate that and pmlb should ignore the column based on it.

Besides that, I think it should still be classification task instead of regression task one beacuse:

1. drinks has 16 unique values in 345 samples
2. It was considered as classification benchmark in the beginning ( From the important note in OpenML: Researchers who wish to use this dataset as a classification benchmark should follow the method used in experiments by the donor (Forsyth & Rada, 1986, Machine learning: applications in expert systems and information retrieval))

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I think we should remove the train/test selector column completely to avoid serious downstream errors. Plus, this column (despite being "not entirely random") does not add meaningful information to the data.

In this survey (pdf), they discussed papers listed on the UCI page that cited the dataset. Many studies used it incorrectly. A few other studies (Turney, Tang et al.), dichotomize the 6th variable (number of alcoholic drinks) using 3 as the numeric threshold (x6 < 3 vs x6 >= 3). If we want to keep the task as classification, I think we should use this threshold and note in the metadata description of target how it's dichotomized.

(Note that the original study used different threshold values in different experiments.)

Alternatively, we can have both datasets bupa_class and bupa_reg for two different tasks.

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I fixed this issue with commits above.

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