Add K-Nearest Neighbors classifier

[poorva0405]

Description

This PR adds a K-Nearest Neighbors (KNN) classifier implementation to the machinelearning package.

Features

• Implements KNN classification using Euclidean distance.
• Supports training through fit().
• Supports prediction for single and batch samples.
• Uses deterministic tie-breaking when multiple classes receive the same number of votes.
• Includes comprehensive input validation.
• Includes JUnit 5 tests covering normal and edge cases.
• Includes Javadocs for all public APIs.

Closes #7562

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized it.
• All filenames are in PascalCase.
• All functions and variable names follow Java naming conventions.
• All new algorithms have a URL in their comments that points to Wikipedia or other similar explanations.
• All new algorithms include a corresponding test class that validates their functionality.
• All new code is formatted with clang-format -i --style=file path/to/your/file.java

[codecov-commenter]

Codecov Report

❌ Patch coverage is 96.92308% with 2 lines in your changes missing coverage. Please review.
✅ Project coverage is 80.66%. Comparing base (6ec6339) to head (d75cae5).

Files with missing lines	Patch %	Lines
...ealgorithms/machinelearning/KNearestNeighbors.java	96.92%	0 Missing and 2 partials ⚠️

Additional details and impacted files

@@             Coverage Diff              @@
##             master    #7563      +/-   ##
============================================
+ Coverage     80.61%   80.66%   +0.04%     
- Complexity     7497     7526      +29     
============================================
  Files           816      817       +1     
  Lines         24097    24162      +65     
  Branches       4741     4759      +18     
============================================
+ Hits          19427    19491      +64     
  Misses         3907     3907              
- Partials        763      764       +1     

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[AKASH02-byte]

Left an inline comment regarding exception checking in KNearestNeighbors.java. Overall, the implementation and tests look clean!

[alxkm]

Solid PR - clean implementation, good tests.

One change requested: move the k > trainingFeatures.length check into fit(), per the thread on line 168.

Improvements (non-blocking):

• fields are declared mid-class, move them to the top next to k
• fit() stores the caller's arrays directly — a defensive copy would be safer
• the two "not fitted" null checks in predict() can be collapsed into one
• Neighbor could be a record

Nice tests coverage.

[poorva0405]

Hi @alxkm, I’ve addressed the requested changes, including moving the k > trainingFeatures.length validation to fit() and implementing the additional improvements discussed.

All 7 CI checks are now passing. Could you please take another look and re-review the PR when you get a chance?

Thank you for the feedback!

[alxkm]

Looks good. Thank you for the contribution.