Implement K-Medoids clustering algorithm #13488

[rohitbansal2005]

Describe your change:

• Add an algorithm

Implemented the K-Medoids clustering algorithm in Python.
This algorithm is similar to K-Means but uses actual data points as cluster centers (medoids),
making it more robust to noise and outliers.
Includes usage example, optional plotting, and doctest.

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.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes Implement K-Medoids Clustering Algorithm #13488".

[algorithms-keeper]

Click here to look at the relevant links ⬇️

🔗 Relevant Links

Repository:

• Contributing guidelines
• Project Euler solution guidelines

Python:

• Formatted string literals (f-strings)
• Type hints
• doctest
• unittest
• pytest

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[algorithms-keeper]

As there is no test file in this pull request nor any test function or class in the file machine_learning/k_medoids.py, please provide doctest for the function get_initial_medoids

Please provide return type hint for the function: get_initial_medoids. If the function does not return a value, please provide the type hint as: def function() -> None:

Please provide type hint for the parameter: data

Please provide descriptive name for the parameter: k

Please provide type hint for the parameter: k

Please provide type hint for the parameter: seed

[algorithms-keeper]

As there is no test file in this pull request nor any test function or class in the file machine_learning/k_medoids.py, please provide doctest for the function assign_clusters

Please provide return type hint for the function: assign_clusters. If the function does not return a value, please provide the type hint as: def function() -> None:

Please provide type hint for the parameter: data

Please provide type hint for the parameter: medoids

[algorithms-keeper]

As there is no test file in this pull request nor any test function or class in the file machine_learning/k_medoids.py, please provide doctest for the function revise_medoids

Please provide return type hint for the function: revise_medoids. If the function does not return a value, please provide the type hint as: def function() -> None:

Please provide type hint for the parameter: data

Please provide descriptive name for the parameter: k

Please provide type hint for the parameter: k

Please provide type hint for the parameter: cluster_assignment

[algorithms-keeper]

As there is no test file in this pull request nor any test function or class in the file machine_learning/k_medoids.py, please provide doctest for the function compute_heterogeneity

Please provide return type hint for the function: compute_heterogeneity. If the function does not return a value, please provide the type hint as: def function() -> None:

Please provide type hint for the parameter: data

Please provide descriptive name for the parameter: k

Please provide type hint for the parameter: k

Please provide type hint for the parameter: medoids

Please provide type hint for the parameter: cluster_assignment

[algorithms-keeper]

As there is no test file in this pull request nor any test function or class in the file machine_learning/k_medoids.py, please provide doctest for the function kmedoids

Please provide return type hint for the function: kmedoids. If the function does not return a value, please provide the type hint as: def function() -> None:

Please provide type hint for the parameter: data

Please provide descriptive name for the parameter: k

Please provide type hint for the parameter: k

Please provide type hint for the parameter: initial_medoids

Please provide type hint for the parameter: maxiter

Please provide type hint for the parameter: verbose

[algorithms-keeper]

As there is no test file in this pull request nor any test function or class in the file machine_learning/k_medoids.py, please provide doctest for the function plot_clusters

Please provide return type hint for the function: plot_clusters. If the function does not return a value, please provide the type hint as: def function() -> None:

Please provide type hint for the parameter: data

Please provide type hint for the parameter: medoids

Please provide type hint for the parameter: cluster_assignment