Optimize and enhancing TimeSeriesSplit class for clarity and performance #4409 #4410
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This commit introduces several optimizations and enhancements to the TimeSeriesSplit class, designed to improve clarity, maintainability, and performance. The modifications ensure that the class remains fully functional and integrates smoothly with existing workflows while adhering to best practices in software development. Key Changes: - Streamlined parameter defaults: Ensured `forecast_horizon` defaults to 1 when unspecified to prevent undefined behaviors. - Improved test size calculation: Refined the logic for calculating `test_size` to depend on whether `n_series` is provided, enhancing the flexibility and applicability of the class. - Refined empty data handling: The split method now has clearer conditions for handling cases where either `X` or `y` are empty or None, ensuring robust behavior in edge cases. - Enhanced validation: Integrated checks using `are_ts_parameters_valid_for_split` before proceeding with splits to ensure the parameters are appropriate for the data size and intended number of splits. - Documentation improvements: Expanded and clarified docstrings throughout the class to provide better guidance and ensure the intentions and functionality of each component are well understood. These changes aim to enhance the usability and effectiveness of the TimeSeriesSplit class in practical time series analysis scenarios.
Optimize and enhance TimeSeriesSplit class for clarity and performance
|
|
|
Fixes #4409 |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Made optimizations and enhancements to the TimeSeriesSplit class, designed to improve clarity, maintainability, and performance. The modifications ensure that the class remains fully functional and integrates smoothly with existing workflows while adhering to best practices in software development.
Key Changes:
forecast_horizondefaults to 1 when unspecified to prevent undefined behaviors.test_sizeto depend on whethern_seriesis provided, enhancing the flexibility and applicability of the class.Xoryare empty or None, ensuring robust behavior in edge cases.are_ts_parameters_valid_for_splitbefore proceeding with splits to ensure the parameters are appropriate for the data size and intended number of splits.These changes aim to enhance the usability and effectiveness of the TimeSeriesSplit class in practical time series analysis scenarios.