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Describe your change:

  • Add an algorithm
  • Fix a bug or typo in an existing algorithm
  • Add or change doctests
  • Documentation change

Description

This pull request adds a Ridge Regression algorithm with L2 regularization, implemented using batch gradient descent.

The implementation:

  • Is written from scratch without using external machine learning libraries
  • Applies L2 regularization while excluding the bias/intercept term
  • Uses clear function and variable naming with Python type hints
  • Includes input validation and comprehensive doctests
  • Is implemented as a pure algorithm with no file I/O, printing, or plotting

Reference:
https://en.wikipedia.org/wiki/Ridge_regression


Checklist:

  • I have read CONTRIBUTING.md.
  • This pull request is all my own work -- I have not plagiarized.
  • I know that pull requests will not be merged if they fail the automated tests.
  • This PR only changes one algorithm file.
  • All new Python files are placed inside an existing directory.
  • All filenames are in all lowercase characters with no spaces or dashes.
  • All functions and variable names follow Python naming conventions.
  • All function parameters and return values are annotated with Python type hints.
  • All functions have doctests that pass the automated testing.
  • All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
  • This pull request resolves one or more open issues (not applicable).

@algorithms-keeper algorithms-keeper bot added tests are failing Do not merge until tests pass awaiting reviews This PR is ready to be reviewed labels Dec 15, 2025
@algorithms-keeper algorithms-keeper bot removed the tests are failing Do not merge until tests pass label Dec 15, 2025
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