from typing import Any, Dict, List
from aeon.classification.feature_based import TSFreshClassifier
from sklearn.ensemble import RandomForestClassifier
from ml_grid.pipeline.data import pipe
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class TSFreshClassifier_class:
"""A wrapper for the aeon TSFreshClassifier time-series classifier."""
def __init__(self, ml_grid_object: pipe):
"""Initializes the TSFreshClassifier_class.
Args:
ml_grid_object (pipe): The main data pipeline object, which contains
data and global parameters.
"""
verbose_param = ml_grid_object.verbose
random_state_val = ml_grid_object.global_params.random_state_val
n_jobs_model_val = ml_grid_object.global_params.n_jobs_model_val
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self.algorithm_implementation: TSFreshClassifier = TSFreshClassifier()
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self.method_name: str = "TSFreshClassifier"
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self.parameter_space: Dict[str, List[Any]] = {
"default_fc_parameters": ["minimal", "efficient", "comprehensive"],
"relevant_feature_extractor": [True, False],
"estimator": [None, RandomForestClassifier(n_estimators=200)],
"verbose": [verbose_param],
"n_jobs": [n_jobs_model_val],
"chunksize": [None, 10, 100],
"random_state": [random_state_val],
}