Tabular

TabularTaskManager(task, data[, pipeline, ...])	Default task manager for tabular data.
pipelines.SimpleTabularPipeline(task, mask, ...)	Default tabular pipeline.
processors.ScalerAndEncoder(mask)	Applies OneHotEncoder/OrdinalEncoder on low/high cardinality categorical features and StandardScaler on numerical features.
processors.MultiModalEncoder(mask)	Applies different types of encodings on numerical, categorical, text and date/datetime features.
processors.LabelDecoder()	Label encoder/decoder to be used for encoding labels as integers and vice versa.
learners.SuperLearner(task[, ...])	Tabular learner which employs StackingModel for construction of meta estimator.
learners.OptunaLearner(task[, model_class, ...])	OptunaLerner select the best hyperparameters for the given model using the Optuna Framework.
learners.PlainLearner(task[, model_class, ...])	PlainLearner trains a model using provided or default hyperparameters.
models.HistGradientBoostingClassifier([...])	Wrapper around sklearn.ensemble.HistGradientBoostingClassifier.
models.HistGradientBoostingRegressor([...])	Wrapper around sklearn.ensemble.HistGradientBoostingRegressor.
models.StackingClassifier(estimators, ...[, ...])	Small wrapper around sklearn.ensemble.StackingClassifier.
models.StackingRegressor(estimators, ...[, ...])	Small wrapper around sklearn.ensemble.StackingRegressor.