ml_grid.model_classes.TPOTClassifierWrapper

TPOT Classifier Wrapper.

This module provides a scikit-learn compatible wrapper for TPOTClassifier.

Attributes

TPOTClassifier
logger

Classes

TPOTClassifierWrapper

A scikit-learn compatible wrapper for TPOTClassifier.

Module Contents

ml_grid.model_classes.TPOTClassifierWrapper.TPOTClassifier = None

ml_grid.model_classes.TPOTClassifierWrapper.logger

class ml_grid.model_classes.TPOTClassifierWrapper.TPOTClassifierWrapper(generations: int = 5, population_size: int = 20, offspring_size: int | None = None, mutation_rate: float = 0.9, crossover_rate: float = 0.1, scoring: str = 'accuracy', cv: int = 5, subsample: float = 1.0, n_jobs: int = -1, max_time_mins: int | None = None, max_eval_time_mins: float = 5, random_state: int = 42, verbosity: int = 2, early_stop: int | None = None)

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

A scikit-learn compatible wrapper for TPOTClassifier.

generations = 5

population_size = 20

offspring_size = None

mutation_rate = 0.9

crossover_rate = 0.1

scoring = 'accuracy'

cv = 5

subsample = 1.0

n_jobs = -1

max_time_mins = None

max_eval_time_mins = 5

random_state = 42

verbosity = 2

early_stop = None

model_ = None

fit(X: numpy.ndarray | pandas.DataFrame, y: numpy.ndarray | pandas.Series, **kwargs) → TPOTClassifierWrapper

predict(X: numpy.ndarray | pandas.DataFrame) → numpy.ndarray

predict_proba(X: numpy.ndarray | pandas.DataFrame) → numpy.ndarray