Supported Estimators
Currently supported
| Category |
Estimators |
| Linear models |
Ridge, Lasso, LinearRegression, LogisticRegression, and other linear models |
| Neural networks |
MLPRegressor, MLPClassifier |
| Trees |
DecisionTreeRegressor, DecisionTreeClassifier |
| Tree ensembles (sklearn) |
RandomForestRegressor, RandomForestClassifier, GradientBoostingRegressor, GradientBoostingClassifier, HistGradientBoostingRegressor, HistGradientBoostingClassifier |
| LightGBM |
LGBMRegressor, LGBMClassifier (columnar tensors or native text) |
| XGBoost |
XGBRegressor, XGBClassifier (columnar tensors or native JSON) |
| Gaussian processes |
GaussianProcessRegressor, GaussianProcessClassifier (including composite kernels) |
| Preprocessing |
StandardScaler, MinMaxScaler, RobustScaler |
| Composition |
Pipeline, TransformedTargetRegressor |
Not yet implemented
| Category |
Estimators |
| Boosting |
CatBoost |
| Meta-estimators |
VotingClassifier, StackingRegressor, etc. |
| Decomposition |
PCA and other decomposition transforms |
Open an issue or PR if you need any of these.
Not planned