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
New discrimination procedure of location model for handling large categorical variables
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DOI: 10.17576/jsm-2017-4606-20
Abstract: The location model proposed in the past is a predictive discriminant rule that can classify new observations into one of two predefined groups based on mixtures of continuous and categorical variables. The ability of location… read more here.
Keywords: location model; categorical variables; large categorical; model ... See more keywords