This work experiments with three clustering techniques in Python, including one from either hierarchical and partitional techniques.
$ pip3 install -r requirements.txtCustom hyperparameters in a textfile i.e. "./configs/config.txt".
$ python3 experiments.py ./configs/config.txtA results folder will contain a timestamp directory with the latest results.
- Iris (http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_iris.html)
- Breast Cancer (http://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