from typing import Any, Dict, List
from aeon.classification.feature_based import SummaryClassifier
from sklearn.ensemble import RandomForestClassifier
from ml_grid.pipeline.data import pipe
[docs]
class SummaryClassifier_class:
"""A wrapper for the aeon SummaryClassifier time-series classifier.
This class provides a consistent interface for the SummaryClassifier,
including defining a hyperparameter search space.
Attributes:
algorithm_implementation: An instance of the aeon SummaryClassifier.
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: SummaryClassifier
[docs]
parameter_space: Dict[str, List[Any]]
def __init__(self, ml_grid_object: pipe):
"""Initializes the SummaryClassifier_class.
Args:
ml_grid_object (pipe): An instance of the main data pipeline object.
"""
n_jobs_model_val = ml_grid_object.global_params.n_jobs_model_val
random_state_val = ml_grid_object.global_params.random_state_val
self.algorithm_implementation = SummaryClassifier()
self.method_name = "SummaryClassifier"
self.parameter_space = {
"summary_functions": [
"mean",
"std",
"min",
"max",
"median",
"sum",
"skew",
"kurt",
"var",
"mad",
"sem",
"nunique",
"count",
],
"summary_quantiles": [None, [0.25, 0.5, 0.75]],
"estimator": [None, RandomForestClassifier(n_estimators=200)],
"n_jobs": [n_jobs_model_val],
"random_state": [random_state_val],
}