data mining methodology development de wang jue (6 résultats)

Taschenbuch. Etat : Neu. DATA MINING METHODOLOGY DEVELOPMENT | CLASSIFICATION CASE STUDY ON MARS CRATERS DETECTION AND VISUALIZATION ANALYSIS USING SAMMON''S MAPPING | Jue Wang | Taschenbuch | 104 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783843364737 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

paperback. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data Mining is a tool that extracts useful and novel patterns from great amounts of data. It usually involves 4 tasks: Classification, Clustering, Association Rule Learning, and Regression. Two major branches of research are addressed in this book. In the first chapter several Classification methods are applied on a real-world data set, the Mars crater data set. The goal of this case study is to improve the accuracy of the crater detection on the remote sensing images of Mars. In the second chapter Sammon's Mapping method is studied and improved. Sammon's Mapping is a projection method which simulates the high-dimension space to a low- dimension one. The motivation of this project is to visualize the internal struture of a data set and facilitate the clustering operation on the data set. After the low-dimension Sammon's Mapped space has been created the number of clusters can be observed. An external measurement of the Clustering result is also implemented in the project. This measurement objectively shows the accuracy of Clustering. With all the steps to implement the Sammon's Mapping, a pipeline is established. 104 pp. Englisch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Wang JueJue Wang was born in Shanghai, China. She received the M.S. Degree in Computer Science from University of Massachusetts Boston, USA. During the time in the graduate school, she organized an association, Women in Science,.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Data Mining is a tool that extracts useful and novel patterns from great amounts of data. It usually involves 4 tasks: Classification, Clustering, Association Rule Learning, and Regression. Two major branches of research are addressed in this book. In the first chapter several Classification methods are applied on a real-world data set, the Mars crater data set. The goal of this case study is to improve the accuracy of the crater detection on the remote sensing images of Mars. In the second chapter Sammon''s Mapping method is studied and improved. Sammon''s Mapping is a projection method which simulates the high-dimension space to a low- dimension one. The motivation of this project is to visualize the internal struture of a data set and facilitate the clustering operation on the data set. After the low-dimension Sammon''s Mapped space has been created the number of clusters can be observed. An external measurement of the Clustering result is also implemented in the project. This measurement objectively shows the accuracy of Clustering. With all the steps to implement the Sammon''s Mapping, a pipeline is established.Books on Demand GmbH, Überseering 33, 22297 Hamburg 104 pp. Englisch.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data Mining is a tool that extracts useful and novel patterns from great amounts of data. It usually involves 4 tasks: Classification, Clustering, Association Rule Learning, and Regression. Two major branches of research are addressed in this book. In the first chapter several Classification methods are applied on a real-world data set, the Mars crater data set. The goal of this case study is to improve the accuracy of the crater detection on the remote sensing images of Mars. In the second chapter Sammon's Mapping method is studied and improved. Sammon's Mapping is a projection method which simulates the high-dimension space to a low- dimension one. The motivation of this project is to visualize the internal struture of a data set and facilitate the clustering operation on the data set. After the low-dimension Sammon's Mapped space has been created the number of clusters can be observed. An external measurement of the Clustering result is also implemented in the project. This measurement objectively shows the accuracy of Clustering. With all the steps to implement the Sammon's Mapping, a pipeline is established.