Clustering Categorical Data Using Community Detection Techniques
With the advent of the k-modes algorithm, the toolbox for clustering categorical data has an efficient tool that scales linearly in the number of data items. However, random initialization of cluster centers in k-modes makes it hard to reach a good clustering without resorting to many trials. Recent...
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| Format: | Article |
| Language: | English |
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Hindawi Limited
2017-01-01
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| Series: | Computational Intelligence and Neuroscience |
| Online Access: | http://dx.doi.org/10.1155/2017/8986360 |