However, the implementation of many of these techniques is challenging due to the fact that much of the data contained in today's databases is categorical in nature. While there have been recent advances in alg
Clustering Algorithms for Categorical Data Sets[聚类算法分类数据集](PPT-50),文档标题《Clustering Algorithms for Categorical Data Sets[聚类算..
Python implementations of the k-modes and k-prototypes clustering algorithms. Relies on numpy for a lot of the heavy lifting. k-modes is used for clustering categorical variables. It defines clusters based on the number of matching categories between data points. (This is in contrast to the mo...
Makwana, Partitioning clustering algorithms for handling numerical and categorical data: a review, 2013, 1311.7219v1Partitioning clustering algorithms for handling numerical and categorical data a reviewfDB]. Kodinariya T M,Makwana P R. http://arxiv.org/abs/1311.7219v2 . 2013...
For either continual or categorical data clustering, most of clustering algorithms rely on optimizing a single objective function such as the intra-distance within a cluster to obtain the data partition. For example, genetic algorithm (GA) based clustering method which is based on the rule of Darw...
Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data - nicodv/kmodes
Many metaheuristic algorithms have recently been reported in addition to the above-discussed algorithms for numerical and real-world engineering design optimization problems, including data clustering. For instance, ant colony optimization35, firefly algorithm36,37, flower pollination algorithm38, grey wolf...
2. 聚类算法选择或设计(Clustering Algorithms) 算法的选择,往往伴随着相似度计算方法的选择。在文本挖掘中,最常用的相似度计算方法是余弦相似度。聚类算法有很多种,但是没有一个通用的算法可以解决所有的聚类问题。因此,需要认真研究要解决的问题的特点,以选择合适的算法。后面会有对各种文本聚类算法的介绍。
Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data - huangyujiesufe/kmodes
Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data - nicodv/kmodes