Pulabaigari viswanath (13 risultati)
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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EUR 76,47
EUR 3,42 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: New.
Scalable Non-Parametric Pattern Recognition Techniques For Data Mining: Fast Non-Parametric Classification And Clustering Methods For Large Data Sets
Veluru, Suresh; Pulabaigari, Viswanath; Veluru, Suresh; Pulabaigari, Viswanath
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 99,04
EUR 11,68 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: Brand New. 116 pages. 8.66x5.91x0.27 inches. In Stock.
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 103,05
EUR 11,68 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: Brand New. 140 pages. 8.66x5.91x0.32 inches. In Stock.
Scalable Non-Parametric Pattern Recognition Techniques For Data Mining: Fast Non-Parametric Classification And Clustering Methods For Large Data Sets
Veluru, Suresh; Pulabaigari, Viswanath; Veluru, Suresh; Pulabaigari, Viswanath
- Brossura
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 106,57
EUR 11,68 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: Brand New. 116 pages. 8.66x5.91x0.27 inches. In Stock.
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Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
Contatta il venditoreVenditore con 4 stelleCondizione: Usato - Come nuovo
EUR 156,36
EUR 29,19 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
- Brossura
- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 76,52
EUR 7,59 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand.
- Brossura
- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 79,55
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND.
- Brossura
- Print on Demand
Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 41,05
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Veluru SureshDr. Suresh Veluru is a postdoctoral fellow at University of New Brunswick,Canada.He received his PhD from Indian Institute of Technology Guwahati, India in 2009. Dr. P. Viswanath is a Prof…essor and Dean R&D (El.
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- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 68,00
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Nearest neighbor classifier (NNC), a non-parametric pattern classification technique is not only simple to use, but often shows good performance. It is used in several domains, like data mining, machine learning, image/video/audio…data analysis and retrieval, etc. It has some shortcomings or limitations, like it can be biased due to curse of dimensionality effect, huge computational requirements, etc. With large number of training instances it can achieve a better classification accuracy. But, this can worse the computational burden. The monograph presents a series of techniques whereby number of training instances can be artificially increased and can be stored in compact data representation schemes. This means, training set size can be virtually increased, but computational burden is not. The monograph presents, mainly, pattern synthesis techniques called partition based pattern synthesis and overlap based pattern synthesis, and their respective compact data structures. It is shown, both theoretically and experimentally that the proposed methods are effective. The monograph also presents some other improvements to NNC and presents a constant time NNC also. 184 pp. Englisch.
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Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 46,18
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kishor Kumar GullaDr. G.Kishor Kumar recieved M.Tech and Ph.D from JNTUA, Ananthapuramu. He is working as Professor and Head of the Department of Information Technology at Rajeev Gandhi Memorial Colleg…e of Engineering and Technology..
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- Print on Demand
Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 55,21
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Pulabaigari ViswanathP. Viswanth received his M.Tech from IIT-Madras, and Ph.D.(best thesis award given) from IISc-Bangalore. He worked at IIT-Guwahati from 2005 to 2008. Since then he is working as a…Professor and Dean, R&D (Electri.
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- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 68,00
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Nearest neighbor classifier (NNC), a non-parametric pattern classification technique is not only simple to use, but often shows good performance. It is used in several domains, like data mining, machine learning, image/video/audio data… analysis and retrieval, etc. It has some shortcomings or limitations, like it can be biased due to curse of dimensionality effect, huge computational requirements, etc. With large number of training instances it can achieve a better classification accuracy. But, this can worse the computational burden. The monograph presents a series of techniques whereby number of training instances can be artificially increased and can be stored in compact data representation schemes. This means, training set size can be virtually increased, but computational burden is not. The monograph presents, mainly, pattern synthesis techniques called partition based pattern synthesis and overlap based pattern synthesis, and their respective compact data structures. It is shown, both theoretically and experimentally that the proposed methods are effective. The monograph also presents some other improvements to NNC and presents a constant time NNC also.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 184 pp. Englisch.
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- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 68,00
EUR 61,46 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Nearest neighbor classifier (NNC), a non-parametric pattern classification technique is not only simple to use, but often shows good performance. It is used in several domains, like data mining, machine learning, image/video/audio data…analysis and retrieval, etc. It has some shortcomings or limitations, like it can be biased due to curse of dimensionality effect, huge computational requirements, etc. With large number of training instances it can achieve a better classification accuracy. But, this can worse the computational burden. The monograph presents a series of techniques whereby number of training instances can be artificially increased and can be stored in compact data representation schemes. This means, training set size can be virtually increased, but computational burden is not. The monograph presents, mainly, pattern synthesis techniques called partition based pattern synthesis and overlap based pattern synthesis, and their respective compact data structures. It is shown, both theoretically and experimentally that the proposed methods are effective. The monograph also presents some other improvements to NNC and presents a constant time NNC also.
