ISBN: 9786203028614 - data mining technique and applications: mining method for long pattern from database (5 resultados)

Taschenbuch. Condición: Neu. Data Mining Technique and Applications | Mining Method for Long Pattern from Database | Monali Vasantarao Deshmukh (u. a.) | Taschenbuch | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786203028614 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Mining high utility item sets from a transactional database refers to the discovery of item sets with high utility like profits. Although a number of relevant algorithms have been proposed in recent years, they incur the problem of producing a large number of candidate item sets for high utility item sets. Such a large number of candidate item sets degrades the mining performance in terms of execution time and space requirement. The situation may become worse when the database contains lots of long transactions or long high utility item sets.In this Book , we propose algorithm namely Improved mining algorithm (Utility Pattern Growth plus) for mining high utility item sets with a set of effective strategies for pruning candidate item sets. The information of high utility item sets is maintained in a tree-based data structure named UP-Tree (Utility Pattern Tree) such that candidate item sets can be generated efficiently with only two scans of database. The performance of UP-Growth and UP Growth+ is compared with the state-of-the-art algorithms on many types of both real and synthetic datasets. 64 pp. Englisch.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Mining high utility item sets from a transactional database refers to the discovery of item sets with high utility like profits. Although a number of relevant algorithms have been proposed in recent years, they incur the problem of producing a large number of candidate item sets for high utility item sets. Such a large number of candidate item sets degrades the mining performance in terms of execution time and space requirement. The situation may become worse when the database contains lots of long transactions or long high utility item sets.In this Book , we propose algorithm namely Improved mining algorithm (Utility Pattern Growth plus) for mining high utility item sets with a set of effective strategies for pruning candidate item sets. The information of high utility item sets is maintained in a tree-based data structure named UP-Tree (Utility Pattern Tree) such that candidate item sets can be generated efficiently with only two scans of database. The performance of UP-Growth and UP Growth+ is compared with the state-of-the-art algorithms on many types of both real and synthetic datasets. …

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Vasantarao Deshmukh MonaliProf. Monali Deshmukh completed her graduate studies from Mumbai university in computer science engg. and having more than 10 year experience as, Asst. Professor in SCOE, Kharghar. She authored/co-authored f. …

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Mining high utility item sets from a transactional database refers to the discovery of item sets with high utility like profits. Although a number of relevant algorithms have been proposed in recent years, they incur the problem of producing a large number of candidate item sets for high utility item sets. Such a large number of candidate item sets degrades the mining performance in terms of execution time and space requirement. The situation may become worse when the database contains lots of long transactions or long high utility item sets.In this Book , we propose algorithm namely Improved mining algorithm (Utility Pattern Growth plus) for mining high utility item sets with a set of effective strategies for pruning candidate item sets. The information of high utility item sets is maintained in a tree-based data structure named UP-Tree (Utility Pattern Tree) such that candidate item sets can be generated efficiently with only two scans of database. The performance of UP-Growth and UP Growth+ is compared with the state-of-the-art algorithms on many types of both real and synthetic datasets.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. …