Fix KNN Classification Logic and Optimize Class Count Aggregation #259
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WalkthroughThe changes update the KNN classification logic in Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant KNN
participant Labels
User->>KNN: Request prediction with input and k
KNN->>KNN: Find k nearest neighbor indices
KNN->>KNN: Collect indices, round labels, count votes
KNN->>Labels: Access label for each neighbor
KNN->>KNN: Fold to select class with highest count (tie: pick smaller label)
KNN-->>User: Return predicted class
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Actionable comments posted: 1
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.coderabbit.yml(1 hunks)delta/src/algorithms.rs(1 hunks)
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.coderabbit.yml (1)
3-8:❓ Verification inconclusive
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446-452: LGTM! Improved tie-breaking logic for class prediction.The new fold-based approach with tie-breaking logic is well-implemented. It correctly selects the class with the highest vote count and breaks ties by choosing the smaller class label, which provides deterministic behavior.
| let k_indices_vec: Vec<usize> = k_indices.collect(); | ||
| for idx in k_indices_vec.iter().cycle().take(self.k) { | ||
| let label = y_train[*idx]; | ||
| let label_int = label.round() as usize; | ||
| *class_counts.entry(label_int).or_insert(0) += 1; | ||
| } |
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Remove unnecessary cycle() usage that could cause incorrect vote counting.
The use of .cycle().take(self.k) is problematic and unnecessary. Since k_indices is already created with .take(self.k) on line 432, it should contain exactly k elements. Using cycle() could theoretically repeat indices if fewer neighbors are found, leading to incorrect vote counting.
Apply this diff to fix the issue:
- let k_indices_vec: Vec<usize> = k_indices.collect();
- for idx in k_indices_vec.iter().cycle().take(self.k) {
+ for idx in k_indices {The label rounding improvement on line 441 is excellent for handling floating-point class labels.
Committable suggestion skipped: line range outside the PR's diff.
🤖 Prompt for AI Agents
In delta/src/algorithms.rs around lines 438 to 443, remove the use of .cycle()
when iterating over k_indices_vec because k_indices already contains exactly
self.k elements. Replace the for loop to iterate directly over k_indices_vec
without cycling to avoid repeating indices and incorrect vote counting.
Summary by CodeRabbit
Bug Fixes
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