Isbn: 9783330845794 - improving the efficiency of c4.5 algorithm for data mining prediction (5 risultati)

Condizione: New.

Taschenbuch. Condizione: Neu. Improving The Efficiency Of C4.5 Algorithm For Data Mining Prediction | Radhwan Hussein Alsagheer | Taschenbuch | 88 S. | Englisch | 2017 | Noor Publishing | EAN 9783330845794 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A decision tree is an important classification technique in data mining classification. Decision trees have proved to be valuable tools for the classification, description, and generalization of data. Work on building decision trees for datasets exists in multiple disciplines such as signal processing, pattern recognition, decision theory, statistics, machine learning and artificial neural networks. This thesis deals with the problem of finding the parameter settings of decision tree algorithm in order to build accurate, small trees, and to reduce execution time for a given domain. 88 pp. Englisch. …

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -A decision tree is an important classification technique in data mining classification. Decision trees have proved to be valuable tools for the classification, description, and generalization of data. Work on building decision trees for datasets exists in multiple disciplines such as signal processing, pattern recognition, decision theory, statistics, machine learning and artificial neural networks. This thesis deals with the problem of finding the parameter settings of decision tree algorithm in order to build accurate, small trees, and to reduce execution time for a given domain.Books on Demand GmbH, Überseering 33, 22297 Hamburg 88 pp. Englisch.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A decision tree is an important classification technique in data mining classification. Decision trees have proved to be valuable tools for the classification, description, and generalization of data. Work on building decision trees for datasets exists in multiple disciplines such as signal processing, pattern recognition, decision theory, statistics, machine learning and artificial neural networks. This thesis deals with the problem of finding the parameter settings of decision tree algorithm in order to build accurate, small trees, and to reduce execution time for a given domain.…