<jupyter_start><jupyter_text>Clustering in Scikit-learnhttps://scikit-learn.org/stable/modules/clustering.html K-meanshttp://web.stanford.edu/class/ee103/visualizations/kmeans/kmeans.html DBSCAN (Density-based Spatial Clustering of Applications with Noise)https://www.naftaliharris.com/blog/visualizing-dbscan-clustering/  Agglomerative Hierarchical Clustering<jupyter_code>illustration.ahc
illustration.dendrogram<jupyter_output><empty_output><jupyter_text>Cluster Distance<jupyter_code>illustration.cluster_distance<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.10237659963436929, 'fraction_numerical': 0.005484460694698354, 'mean_word_length': 9.745098039215685, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 2, 'lorem ipsum': 0, 'www.': 1, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '14448', 'license': 'MIT', 'n_tokens_mistral': 207, 'n_tokens_neox': 187, 'n_words': 17, 'path': '18 - Unsupervised Learning/01 - Clustering/Part 1 - Some Clustering Algorithms.ipynb', 'repo_name': 'rendywijayaa/Unsupervised_Deep_Learning', 'size': '547'}