ml_grid.model_classes.FLAMLClassifierWrapper

FLAML Classifier Wrapper.

This module provides a scikit-learn compatible wrapper for FLAML’s AutoML.

Attributes

AutoML

logger

Classes

FLAMLClassifierWrapper

A scikit-learn compatible wrapper for FLAML AutoML.

Module Contents

ml_grid.model_classes.FLAMLClassifierWrapper.AutoML = None[source]
ml_grid.model_classes.FLAMLClassifierWrapper.logger[source]
class ml_grid.model_classes.FLAMLClassifierWrapper.FLAMLClassifierWrapper(time_budget: int = 60, metric: str = 'auto', task: str = 'classification', n_jobs: int = -1, eval_method: str = 'auto', split_ratio: float = 0.2, n_splits: int = 5, log_file_name: str = 'flaml.log', seed: int = 42, verbose: int = 0, estimator_list: str | List[str] = 'auto')[source]

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

A scikit-learn compatible wrapper for FLAML AutoML.

time_budget = 60[source]
metric = 'auto'[source]
task = 'classification'[source]
n_jobs = -1[source]
eval_method = 'auto'[source]
split_ratio = 0.2[source]
n_splits = 5[source]
log_file_name = 'flaml.log'[source]
seed = 42[source]
verbose = 0[source]
estimator_list = 'auto'[source]
model_ = None[source]
fit(X: numpy.ndarray | pandas.DataFrame, y: numpy.ndarray | pandas.Series, **kwargs) FLAMLClassifierWrapper[source]
predict(X: numpy.ndarray | pandas.DataFrame) numpy.ndarray[source]
predict_proba(X: numpy.ndarray | pandas.DataFrame) numpy.ndarray[source]