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Publicado por LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659516279ISBN 13: 9783659516276
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
Libro
Condición: New.
Publicado por LAP Lambert Academic Publishing, 2014
ISBN 10: 3659516279ISBN 13: 9783659516276
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Condición: New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book.
Publicado por LAP Lambert Academic Publishing 2014-02, 2014
ISBN 10: 3659516279ISBN 13: 9783659516276
Librería: Chiron Media, Wallingford, Reino Unido
Libro
PF. Condición: New.
Publicado por LAP LAMBERT Academic Publishing Feb 2014, 2014
ISBN 10: 3659516279ISBN 13: 9783659516276
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This project work deals with reality mining and decision tree. Reality mining is the collection and analysis of data where human social behavior is analyzed through machine-sensed environment, with the goal of identifying predictable patterns of behavior. Classification is the process of finding a model that describe and distinguishes data classes, with the purpose of using model to predict the class of objects whose class label is unknown. A decision tree is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. ID3 is mathematical algorithm for building the decision tree. It builds the tree from the top down recursive divide-and-conquer manner, with no backtracking. Advantages of ID3 are it build fast and short tree. Disadvantage is data may be over fitted and over classified if a small sample is tested. Only one attribute at a time is tested for making decision. This project work:- To study the drawback of existing decision tree algorithms. To compare the decision tree with R using existing implementation. To apply and study the decision tree with reality mining 68 pp. Englisch.
Publicado por LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659516279ISBN 13: 9783659516276
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
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PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Publicado por LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659516279ISBN 13: 9783659516276
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Libro Impresión bajo demanda
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This project work deals with reality mining and decision tree. Reality mining is the collection and analysis of data where human social behavior is analyzed through machine-sensed environment, with the goal of identifying predictable patterns of behavior. Classification is the process of finding a model that describe and distinguishes data classes, with the purpose of using model to predict the class of objects whose class label is unknown. A decision tree is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. ID3 is mathematical algorithm for building the decision tree. It builds the tree from the top down recursive divide-and-conquer manner, with no backtracking. Advantages of ID3 are it build fast and short tree. Disadvantage is data may be over fitted and over classified if a small sample is tested. Only one attribute at a time is tested for making decision. This project work:- To study the drawback of existing decision tree algorithms. To compare the decision tree with R using existing implementation. To apply and study the decision tree with reality mining.
Publicado por LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659516279ISBN 13: 9783659516276
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
Libro Impresión bajo demanda
PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Publicado por LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659516279ISBN 13: 9783659516276
Librería: moluna, Greven, Alemania
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rameshkumar K.He has awarded PhD CSE from Alagappa University, India. He is working as Associate Professor at Department of Information Technology, Hindustan University, Chennai, India. His area of Interests are BigData, Larger Scale.