{'fraction_non_alphanumeric': 0.014925373134328358, 'fraction_numerical': 0.0, 'mean_word_length': 5.71, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, '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}}
A Survey of Distributed Clustering Algorithms

Clustering is to divide a set of objects into multiple classes, and each class is made up of similar objects. Traditional centralized clustering algorithms cluster objects stored in a single site, but it cannot satisfy the clustering requirements when objects are distributed. Distributed clustering algorithms can satisfy this need, which extracts a classification mode from distributed objects. This paper classifies and analyzes typical distributed clustering algorithms. Two data sets-Iris and Wine are used to compare several distributed clustering algorithms from two metrics: clustering accuracy and clustering time.