Rstg
STG : Feature Selection using STochastic Gates
'STG' is a method for feature selection in neural network. The procedure is based on probabilistic relaxation of the l0 norm of features, or the count of the number of selected features. The framework simultaneously learns either a nonlinear regression or classification function while selecting a small subset of features. Read more: Yamada et al. (2020) https://proceedings.mlr.press/v119/yamada20a.html.
- Version0.0.1
- R versionunknown
- LicenseMIT
- Needs compilation?No
- Last release12/13/2021
Documentation
Team
Yutaro Yamada
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- Imports1 package