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In this paper, we present a new algorithm. K-meansⅡ to extend the famous K-means algorithm which is efficient only on numerical clustering, by using new cluster ...
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Clustering over categorical attributes is an important yet tough task. In this paper, we present a new algorithm K-meansⅡ to extend the famous K-means algorithm ...
A new clustering criterion to determine the similarity between points with categorical attributes is presented. Furthermore, a new clustering algorithm for ...
A new algorithm K-meansⅡ is presented to extend the famous K-Means algorithm, by using new cluster center definitions and new similarity measures, ...
Dec 7, 2024 · We introduce new dissimilarity measures to deal with categorical objects, replace means of clusters with modes, and use a frequency based method ...
Dec 26, 2024 · KModes is a clustering algorithm used in data science to group similar data points into clusters based on their categorical attributes.
We develop a robust hierarchical clustering algorithm ROCK that employs links and not distances when merging clusters.
This method can find the intrinsic relationship between the different values of the same attribute, and can measure the difference between objects effectively.
Nov 1, 2021 · The K-Modes algorithm modifies the standard K-Means process for clustering categorical data by replacing the notion of distances with ...
It is shown that the traditional clustering algorithms using distance metric between points is not appropriate for boolean and categorical attributes, ...