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
Soft Label With Channel Encoding for Dependent Facial Image Classification
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DOI: 10.1109/access.2022.3145195
Abstract: In classification tasks, training labels are usually specified as one-hot targets which represent each class equally and exclusively. However, this labeling rule is not suitable in some situations. For the dependent classes, one-hot targets are… read more here.
Keywords: one hot; classification; channel encoding; soft label ... See more keywords