from typing import Any, Dict, List
from aeon.classification.dictionary_based._tde import TemporalDictionaryEnsemble
from ml_grid.pipeline.data import pipe
from ml_grid.util.global_params import global_parameters
[docs]
class TemporalDictionaryEnsemble_class:
"""A wrapper for the aeon TemporalDictionaryEnsemble classifier.
This class provides a consistent interface for the
TemporalDictionaryEnsemble classifier, including defining a hyperparameter
search space.
Attributes:
algorithm_implementation: An instance of the aeon
TemporalDictionaryEnsemble classifier.
method_name (str): The name of the classifier method.
parameter_space (Dict[str, List[Any]]): The hyperparameter search space
for the classifier.
"""
[docs]
algorithm_implementation: TemporalDictionaryEnsemble
[docs]
parameter_space: Dict[str, List[Any]]
def __init__(self, ml_grid_object: pipe):
"""Initializes the TemporalDictionaryEnsemble_class.
Args:
ml_grid_object (pipe): An instance of the main data pipeline object.
"""
verbose_param = ml_grid_object.verbose
random_state_val = ml_grid_object.global_params.random_state_val
time_limit_param = global_parameters.time_limit_param
n_jobs_model_val = ml_grid_object.global_params.n_jobs_model_val
self.algorithm_implementation = TemporalDictionaryEnsemble()
self.method_name = "TemporalDictionaryEnsemble"
self.parameter_space = {
"n_parameter_samples": [100, 250, 500],
"max_ensemble_size": [25, 50, 100],
"max_win_len_prop": [0.5, 1.0],
"min_window": [5, 10, 15],
"randomly_selected_params": [25, 50, 75],
"bigrams": [True, False, None],
"dim_threshold": [0.7, 0.85, 0.95],
"max_dims": [10, 20, 30],
"time_limit_in_minutes": time_limit_param,
"contract_max_n_parameter_samples": [100, 250, 500],
"typed_dict": [True, False],
"n_jobs": [n_jobs_model_val],
"random_state": [random_state_val],
}