rubenandrebarreiro/staphylococcus-aureus-image-clustering

🦠 🔬 🧠 A project based in Machine Learning, in the topic of Unsupervised Learning. This project was built using Python, NumPy, SciKit-Learn, Anaconda and Spyder. The scenario of the project was a clustering of several sample images of a bacteria, in order to help the biologists identifying some sample images from them, in sub-groups of each phase of it. It was implemented the K-Means, the DBSCAN, the Bisecting K-Means and the Affinity Propagation clustering methods. The dataset is inspired on some samples of the cellular phases of the Staphylococcus Aureus. The final goal of the project was to implement and tune the Clustering Methods, studying their performances, by computing some Internal and External indicators/metrics, such as, the Silhouette, the Precision, the Recall, the Rand Index, the F1 and the Adjusted Rand Scores, varying some Hyperparameters of the models of the clustering methods. In the final, it was generated some HTML Reports with the several sample images, categorized accordingly to the respective clusters.

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