from typing import Any, Dict, List
from aeon.classification.distance_based import KNeighborsTimeSeriesClassifier
from ml_grid.pipeline.data import pipe
[docs]
class KNeighborsTimeSeriesClassifier_class:
"""A wrapper for the aeon KNeighborsTimeSeriesClassifier."""
def __init__(self, ml_grid_object: pipe):
"""Initializes the KNeighborsTimeSeriesClassifier_class.
Args:
ml_grid_object (pipe): The main data pipeline object, which contains
data and global parameters.
"""
[docs]
self.algorithm_implementation: KNeighborsTimeSeriesClassifier = (
KNeighborsTimeSeriesClassifier()
)
[docs]
self.method_name: str = "KNeighborsTimeSeriesClassifier"
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self.parameter_space: Dict[str, List[Any]] = {
"distance": [
"dtw",
"euclidean",
], # , 'cityblock' 'ctw', 'sqeuclidean','sax' 'softdtw'
"n_neighbors": [2, 3, 5], # [log_med_long]
"n_jobs": [ml_grid_object.global_params.knn_n_jobs],
}
# nb consider probability scoring on binary class eval: CalibratedClassifierCV