This work experiments with three clustering techniques in Python, including one from either hierarchical and partitional techniques.

$ pip3 install -r requirements.txt

Custom hyperparameters in a textfile i.e. "./configs/config.txt".

$ python3 experiments.py ./configs/config.txt

A results folder will contain a timestamp directory with the latest results.

• Iris (http:https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_iris.html)
• Breast Cancer (http:https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(diagnostic))
• Toy Dataset: Noisy circles (https://scikit-learn.org/stable/auto_examples/cluster/plot_cluster_comparison.html)

• Hierarchical: Agglomerative Clustering
• Partitional: K-Means
• Partitional: Gaussian Mixture

Clustering-Alonso.pdf