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fix selection of best categories bucketers.py #116

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Currently, when encoding_method == "ordered" the features are ordered based on the proportion of events in the target variable in ascending order.

Ideally, we would like to keep the categories with highest proportion of events separately, and those with lowest volume of events, then to be dropped

by doing

normalized_counts = normalized_counts[-self.max_n_categories:]

we ensure to keep the top frequent categories

Currently, when encoding_method == "ordered" the features are ordered based on the proportion of events in the target variable in ascending order.

Ideally, we would like to keep the categories with highest proportion of events separately, and those with lowest volume of events, then to be dropped

by doing 

normalized_counts = normalized_counts[-self.max_n_categories:]

we ensure to keep the top frequent categories
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