120 citations · 127 across the 3 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2019★ 120 cited
Encoding high-cardinality string categorical variables
Patricio Cerda, Gaël Varoquaux
Statistical models usually require vector representations of categorical variables, using for instance one-hot encoding. This strategy breaks down when the number of categories gro…
cs.LG2018
Similarity encoding for learning with dirty categorical variables
Patricio Cerda, Gaël Varoquaux, Balázs Kégl
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. "Dirt…