Releases: linkedin/detext
Releases · linkedin/detext
DeText v2.0.8 Release Note
DeText v2.0.6 Release Note
v2.0.5-alpha Release (test)
test automatic release
DeText v1.2.0 Release Note
Currently DeText's design for sparse feature has simple modeling power for sparse features.
- only linear model is applied on sparse features
- there's no interaction between sparse features and dense features (model_score = dense_score + sparse_score)
DeText v1.2.0 resolves the above limitation on sparse feature by
- computing dense representation of sparse features
- allowing interactions between sparse features and wide features
More specifically, the model architecture changes from
dense_score = dense_ftrs -> MLP
sparse_score = sparse_ftrs -> Linear
final_score = dense_score + sparse_score
to
sparse_emb_ftrs = sparse_ftrs -> Dense(sp_emb_size)
all_ftrs = (dense_ftrs, sparse_emb_ftrs) -> Concatenate
final_score= all_ftrs -> MLP
Update logging logic
See #12 for changes