The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, we propose a new cluster validity index (CVI) based on geometrical shape. Classic CVIs are based on a combination of separation and compactness measures and may include a measure of overlap between clusters. The proposed CVI combines measures of compactness and over-lap using n-sphere shape. We conducted experiments on several real data sets from the UCI repository and compared the...
Data clustering is an important task in data mining, image processing and other pattern recognition problems. One of the most popular clustering algorithms is the Fuzzy C-Means (FCM). The performance of the FCM is strongly affected by the selection of the initial centroid clusters. Therefore, choosing a good set of initial centroid clusters is very important for the algorithm. However, it is difficult...
This paper gives a relational fuzzy c-medoids clustering algorithm that is able to partition objects taking into account simultaneously several dissimilarity matrices. The aim is to obtain a collaborative role of the different dissimilarity matrices in order to obtain a final consensus partition. These matrices could have been obtained using different sets of variables and dissimilarity functions...
This paper gives an adaptive version of the fuzzy clustering algorithm based on city-block distances. The proposed method gives a fuzzy partition and a prototype for each cluster by optimizing an adequacy criterion based on an adaptive city-block distance that changes at each algorithm's iteration and is different from one cluster to another. Experiments with real data sets show the usefulness of...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.