cbr_fox.core.cbr_fox

class cbr_fox.core.cbr_fox(metric: str = 'dtw', smoothness_factor: float = 0.2, kwargs: dict = {})

Core class to perform calculations and analysis at technique-level depth.

This class is used to preprocess the provided input data for performing correlation and find the best cases. Its} functionality follows classic AI library guidelines and standards such as scikit-learn and keras.

Parameters:

• metric (str or callable, optional) – The metric to use for correlation (default is “dtw”).

• smoothness_factor (float, optional) – The smoothness factor for preprocessing (default is 0.2).

• kwargs (dict, optional) – Additional keyword arguments for customization.

__init__(self, metric, smoothness_factor, kwargs)

Initializes the cbr_fox class with specified parameters.

__init__(metric: str = 'dtw', smoothness_factor: float = 0.2, kwargs: dict = {})

Initializes the cbr_fox class with specified parameters. :param metric: :param smoothness_factor: :param kwargs:

Methods

__init__([metric, smoothness_factor, kwargs])	Initializes the cbr_fox class with specified parameters.
calculate_analysis(indexes, ...)	Compute analysis results and store them in a record array for reporting and visualization.
calculate_analysis_combined(...)
fit(training_windows, ...)	Perform correlation analysis and identify cases based on the provided data.
get_analysis_report()	Access the analysis report containing the best cases based on the analysis.
get_analysis_report_combined()	Access the combined analysis report containing the best cases based on the combined analysis.
predict(prediction, num_cases, mode)	Perform analysis to identify the best cases based on the provided prediction.