ml_grid.model_classes.AutoGluonClassifier

AutoGluon Classifier Wrapper.

This module provides a scikit-learn compatible wrapper for AutoGluon’s TabularPredictor.

Attributes

`TabularPredictor`
`logger`

Classes

AutoGluonClassifier

A scikit-learn compatible wrapper for AutoGluon TabularPredictor.

Module Contents

ml_grid.model_classes.AutoGluonClassifier.TabularPredictor = None[source]

ml_grid.model_classes.AutoGluonClassifier.logger[source]

class ml_grid.model_classes.AutoGluonClassifier.AutoGluonClassifier(time_limit: int = 120, presets: str | None = None, eval_metric: str = 'accuracy', problem_type: str | None = None, seed: int = 42, verbosity: int = 2, path: str | None = None, excluded_model_types: List[str] | None = None, hyperparameters: dict | None = None)[source]

Bases: sklearn.base.BaseEstimator, sklearn.base.ClassifierMixin

A scikit-learn compatible wrapper for AutoGluon TabularPredictor.

time_limit = 120[source]

presets = None[source]

eval_metric = 'accuracy'[source]

problem_type = None[source]

seed = 42[source]

verbosity = 2[source]

path = None[source]

excluded_model_types = None[source]

hyperparameters = None[source]

predictor_ = None[source]

classes_ = None[source]

model_id = None[source]

timed_out_ = False[source]

fit(X: pandas.DataFrame, y: pandas.Series, **kwargs) → AutoGluonClassifier[source]

predict(X: pandas.DataFrame) → numpy.ndarray[source]

predict_proba(X: pandas.DataFrame) → numpy.ndarray[source]