Mccrosky jesse (6 resultados)

Paperback. Condición: Brand New. 68 pages. 8.66x5.91x0.16 inches. In Stock.

Taschenbuch. Condición: Neu. A New Measure for Clustering Model Selection | Automatic Detection of the Number of Clusters in a Data Set | Jesse McCrosky | Taschenbuch | 68 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838323978 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Typical k-means clustering procedures require a priori knowledge of the number of clusters in the data set. This value can be very difficult to ascertain. Existing heuristic methods work in some cases, but are rarely very reliable. Herein, a new method for determining the number of k-means clusters in a given data set is presented. The algorithm is developed from its theoretical basis and its implementation is examined and compared to existing solutions. 68 pp. Englisch. …

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Typical k-means clustering procedures require a priori knowledge of the number of clusters in the data set. This value can be very difficult to ascertain. Existing heuristic methods work in some cases, but are rarely very reliable. Herein, a new method for determining the number of k-means clusters in a given data set is presented. The algorithm is developed from its theoretical basis and its implementation is examined and compared to existing solutions.…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: McCrosky JesseJesse McCrosky, M.Math completed his Master s Degree in Computer Science at the University of Waterloo. He is currently pursuing a Ph.D. in Community Health and Epidemiology at the University of Saskatchewan and worki.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Typical k-means clustering procedures require a priori knowledge of the number of clusters in the data set. This value can be very difficult to ascertain. Existing heuristic methods work in some cases, but are rarely very reliable. Herein, a new method for determining the number of k-means clusters in a given data set is presented. The algorithm is developed from its theoretical basis and its implementation is examined and compared to existing solutions.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch.…