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Implementing the K-means algorithm from scratch with an OOP approach to cluster an sklearn dataset of fine needle aspirates from the cancer cells of breast cancer patients.

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K-Means Implementation on classic binary classification dataset

This is a repository for a simple implementation of k-means clustering from scratch, working with the classic and simply binary classification dataset of fine needle aspirates from breast cancer patients. Implemented with an OOP approach in Python 3.9

Dataset

The breast cancer Wisconsin diagnostic dataset from the UCI Machine Learning Repository was used. Details can be found here:

https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+(Diagnostic)

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Implementing the K-means algorithm from scratch with an OOP approach to cluster an sklearn dataset of fine needle aspirates from the cancer cells of breast cancer patients.

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