Make the filter_outlier method public

[ishiko732]

The tests for evaluate and evaluate_with_time_series_splits require filter_outlier to be applied to the training set, but this method is currently internal and not publicly accessible.

[gemini-code-assist]

Summary of Changes

Hello @ishiko732, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request exposes the filter_outlier utility function, which was previously restricted to internal crate usage. The primary motivation for this change is to facilitate comprehensive testing of evaluation methods that require this function for data preprocessing, ensuring that the necessary data manipulation logic is available for test environments.

Highlights

• Visibility Change: The filter_outlier function has been changed from pub(crate) to pub, making it publicly accessible outside of its containing crate.
• Test Enablement: This change is necessary to allow tests for evaluate and evaluate_with_time_series_splits to properly apply filter_outlier to training sets, as it was previously an internal method.

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[gemini-code-assist]

Code Review

This pull request correctly makes the filter_outlier function public, which is necessary for its use in tests as described. The changes in src/dataset.rs and src/lib.rs are appropriate for this purpose.

While reviewing, I noticed a potential bug in the prepare_training_data function within src/dataset.rs (line 264), which is outside the scope of this PR's changes. It appears to pass the entire items vector to filter_outlier instead of the trainset derived from partitioning. This could lead to incorrect outlier filtering. This is what it looks like:

(dataset_for_initialization, trainset) = filter_outlier(dataset_for_initialization, items);

It should probably be:

(dataset_for_initialization, trainset) = filter_outlier(dataset_for_initialization, trainset);

This is demonstrated by the correct usage in test_filter_outlier. This could be addressed in a follow-up pull request.

Overall, the changes in this PR are approved.

[L-M-Sherlock]

LGTM