"""Stacked Ensemble Classifier."""
from evalml.model_family import ModelFamily
from evalml.pipelines.components import ElasticNetClassifier
from evalml.pipelines.components.ensemble import StackedEnsembleBase
from evalml.problem_types import ProblemTypes
[docs]class StackedEnsembleClassifier(StackedEnsembleBase):
"""Stacked Ensemble Classifier.
Arguments:
final_estimator (Estimator or subclass): The classifier used to combine the base estimators. If None, uses ElasticNetClassifier.
n_jobs (int or None): Integer describing level of parallelism used for pipelines. None and 1 are equivalent.
If set to -1, all CPUs are used. For n_jobs below -1, (n_cpus + 1 + n_jobs) are used. Defaults to -1.
- Note: there could be some multi-process errors thrown for values of `n_jobs != 1`. If this is the case, please use `n_jobs = 1`.
random_seed (int): Seed for the random number generator. Defaults to 0.
"""
name = "Stacked Ensemble Classifier"
model_family = ModelFamily.ENSEMBLE
"""ModelFamily.ENSEMBLE"""
supported_problem_types = [
ProblemTypes.BINARY,
ProblemTypes.MULTICLASS,
ProblemTypes.TIME_SERIES_BINARY,
ProblemTypes.TIME_SERIES_MULTICLASS,
]
"""[
ProblemTypes.BINARY,
ProblemTypes.MULTICLASS,
ProblemTypes.TIME_SERIES_BINARY,
ProblemTypes.TIME_SERIES_MULTICLASS,
]"""
hyperparameter_ranges = {}
"""{}"""
_default_final_estimator = ElasticNetClassifier