Source code for InidividualTDEClassifier_module

from typing import Any, Dict, List

from aeon.classification.dictionary_based._tde import IndividualTDE
from ml_grid.pipeline.data import pipe


[docs] class IndividualTDE_class: """A wrapper for the aeon IndividualTDE time-series classifier.""" def __init__(self, ml_grid_object: pipe): """Initializes the IndividualTDE_class. Args: ml_grid_object (pipe): The main data pipeline object, which contains data and global parameters. """ random_state_val = ml_grid_object.global_params.random_state_val n_jobs_model_val = ml_grid_object.global_params.n_jobs_model_val
[docs] self.algorithm_implementation: IndividualTDE = IndividualTDE()
[docs] self.method_name: str = "IndividualTDE"
[docs] self.parameter_space: Dict[str, List[Any]] = { "window_size": [5, 10, 15], "word_length": [4, 8, 12], "norm": [True, False], "levels": [1, 2, 3], "igb": [True, False], "alphabet_size": [3, 4, 5], "bigrams": [True, False], "dim_threshold": [0.8, 0.85, 0.9], "max_dims": [15, 20, 25], "typed_dict": [True, False], "n_jobs": [n_jobs_model_val], "random_state": [random_state_val], }