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.
The fuzzy c-means algorithm is a useful technique for clustering real s-dimensional data, but it can not be directly used for partially missing data sets. In this paper, the problem of missing data handling for fuzzy clustering is considered, and a statistical representation of missing attributes is proposed. The approach reduces the statistical analysis of missing attributes to the subsets of the...
K-means clustering is sensitive to starting points and its time cost is expensive for large scale of data, such as audio. Sampling approach is widely applied to find “better” starting points for speeding up the clustering converging procedure. However, how to choose a reasonable sampling-rate remains a problem. In this paper, we reported our initial exploration of locating reasonable sampling-rates...
Clustering is a hot research field in data mining. There are so many methods or algorithms designed for different type data set on which data analysis action operates. Local Agglomerative Characteristic (LAC) based Algorithm, in this paper, is presented for data clustering, which can handle clusters of different size, shapes, and densities, can work well on different distributed and natural variant...
In this paper, we propose a new kernel function that makes use of Riemannian geodesic distance s among data points, and present a Geometric median shift algorithm over Riemannian Manifolds. Relying on the geometric median shift, together with geodesic distances, our approach is able to effectively cluster data points distributed on Riemannian manifolds. In addition to improving the clustering results,...
An algorithm, TBCClustering, is presented in the paper for clustering GML documents using maximal frequent induced subtree patterns. TBCClustering mines the maximal frequent induced subtrees by using the structural information of GML documents, it can get the best minimum support automatically, and then chooses a set of subtree patterns to form the optimistic clustering features. Finally it uses CLOPE...
A great deal of sports data are recording year by year, including training data of athletes, test data of students in sports course, and test data of Physical Health Standard (PHS). In the past, usage of these records is limited to basic statistics analysis. With the development of artificial intelligence and data analysis technologies, sports data analysis became more and more technical. Data mining...
Cognitive maps, one of the hot topic in the research of computational intelligence, have been widely used in knowledge representation and decision-making. In mining of cognitive maps on the basis of data resources, outlier data seriously affect the accuracy of cognitive maps. Therefore, this paper, based on the analysis of traditional ones, proposes a new outlier data detection algorithm. The algorithm...
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.