9786203854022 - Analytical and Statistical Data Mining: Classification Trees di Singh, Amitoj; Sachdeva, Rohit (5 risultati)

Taschenbuch. Condizione: Neu. Analytical and Statistical Data Mining: Classification Trees | Amitoj Singh (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203854022 | 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 -In this book two methods are explored that are used for classification tree to handle large amount of data. In the first method to mine large data sets, a single training data set is be broken into n subsets. A classification tree will be learned from each of these n subsets in parallel. Rules are then be generated from the classification trees. These rules are combined into one rule set. Then the final set of rules are used to classify future unseen data. In the second method, post process the mined information from classification tree in order to extract actions to change the status of classified groups (e.g. customers) from an undesired status (such as attritors) to a desired one (such as loyal). 56 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Singh AmitojDr. Amitoj Singh is an academician working at Maharaja Ranjit Singh Punjab Technical University, Punjab. He is Masters and Doctorate in Computer Science. Dr. Rohit Sachdeva is working as Assistant Professor in MM Modi Col.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book two methods are explored that are used for classification tree to handle large amount of data. In the first method to mine large data sets, a single training data set is be broken into n subsets. A classification tree will be learned from each of these n subsets in parallel. Rules are then be generated from the classification trees. These rules are combined into one rule set. Then the final set of rules are used to classify future unseen data. In the second method, post process the mined information from classification tree in order to extract actions to change the status of classified groups (e.g. customers) from an undesired status (such as attritors) to a desired one (such as loyal).VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book two methods are explored that are used for classification tree to handle large amount of data. In the first method to mine large data sets, a single training data set is be broken into n subsets. A classification tree will be learned from each of these n subsets in parallel. Rules are then be generated from the classification trees. These rules are combined into one rule set. Then the final set of rules are used to classify future unseen data. In the second method, post process the mined information from classification tree in order to extract actions to change the status of classified groups (e.g. customers) from an undesired status (such as attritors) to a desired one (such as loyal).