f93286ffbd8179a8b848c31b5cd25335b28ff0c2
Prior to this change, the find function implementation for the CoverTree class could have potentially returned the wrong result in cases where there were multiple points in the dataset equidistant from p. For example, the current test passed for k=3 but failed to produce the correct result for k=4 (it claimed that 3, 4, 5, and 7 were the 4 closest points to 5 in the dataset rather than 3, 4, 5, and 6). Sorting the neighbors vector before collecting the first k values from it resolved this issue.
Description
A comprehensive library for machine learning and numerical computing. Apply Machine Learning with Rust leveraging first principles.
classificationclusteringmachine-learningmachine-learning-algorithmsmodel-selectionregressionrustrust-langscientific-computingstatistical-learningstatistical-models
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Apache-2.0
2.9 MiB
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Rust
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