Similarity encoding for learning with dirty categorical variables
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DOI: 10.1007/s10994-018-5724-2
Abstract: For statistical learning, categorical variables in a table are usually considered as discrete entities and encoded separately to feature vectors, e.g., with one-hot encoding. “Dirty” non-curated data give rise to categorical variables with a very… read more here.
Keywords: encoding learning; similarity encoding; similarity; categorical variables ... See more keywords