resultados (1 - 19) de 19

Mostrar resultados para

Tipo de artículo


Filtrar por

Condición

Encuadernación

Más atributos

Ubicación del vendedor

Valoración de los vendedores

Ganatra, Amit

Publicado por Omniscriptum Gmbh & Co. Kg. 2012-03-22 (2012)

ISBN 10: 3848419939 ISBN 13: 9783848419937

Nuevo
Tapa blanda

Cantidad disponible: > 20

Vendedor: Blackwell's (Oxford, OX, Reino Unido)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 41,72
Convertir moneda
Gastos de envío: EUR 5,92
De Reino Unido a Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: Omniscriptum Gmbh & Co. Kg. 2012-03-22, 2012. paperback. Condición: New. Nº de ref. del artículo: 9783848419937

Más información sobre este vendedor | Contactar al vendedor 1.

Ganatra, Amit

Publicado por LAP Lambert Academic Publishing (2012)

ISBN 10: 3848419939 ISBN 13: 9783848419937

Nuevo

Cantidad disponible: > 20

Vendedor: Books2Anywhere (Fairford, GLOS, Reino Unido)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 50,98
Convertir moneda
Gastos de envío: EUR 5,93
De Reino Unido a Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP Lambert Academic Publishing, 2012. 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. Nº de ref. del artículo: LQ-9783848419937

Más información sobre este vendedor | Contactar al vendedor 2.

Ganatra, Amit

Publicado por LAP Lambert Academic Publishing (2012)

ISBN 10: 3848419939 ISBN 13: 9783848419937

Nuevo

Cantidad disponible: > 20

Vendedor: Paperbackshop-US (Wood Dale, IL, Estados Unidos de America)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 57,49
Convertir moneda
Gastos de envío: GRATIS
A Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP Lambert Academic Publishing, 2012. PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: LQ-9783848419937

Más información sobre este vendedor | Contactar al vendedor 3.

Ganatra Amit

Publicado por Omniscriptum Gmbh & Co. Kg. 2013-10-17 (2013)

ISBN 10: 3659395870 ISBN 13: 9783659395871

Nuevo
Tapa blanda

Cantidad disponible: > 20

Vendedor: Blackwell's (Oxford, OX, Reino Unido)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 59,88
Convertir moneda
Gastos de envío: EUR 5,92
De Reino Unido a Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: Omniscriptum Gmbh & Co. Kg. 2013-10-17, 2013. paperback. Condición: New. Nº de ref. del artículo: 9783659395871

Más información sobre este vendedor | Contactar al vendedor 4.

Amit Ganatra

Publicado por LAP Lambert Academic Publishing Mrz 2012 (2012)

ISBN 10: 3848419939 ISBN 13: 9783848419937

Nuevo
Tapa blanda

Cantidad disponible: 1

Vendedor: Rheinberg-Buch (Bergisch Gladbach, Alemania)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 49,00
Convertir moneda
Gastos de envío: EUR 17,13
De Alemania a Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP Lambert Academic Publishing Mrz 2012, 2012. Taschenbuch. Condición: Neu. Neuware - In classifying large data set, efficiency and scalability are main issues. Advantages of neural networks include their high tolerance to noisy data, as well as their ability to classify patterns on which they have not been trained. Neural networks are a good choice for most classification and prediction tasks. The necessary complexity of neural networks is one of the most interesting problems in the research. One of the challenges in training MLP is in optimizing weight changes. Advances are introduced in traditional Back Propagation (BP) algorithm, to overcome its limitations. One method is to hybrid GA with BP to optimize weight changes.The objective here is to develop a data classification algorithm that will be used as a general-purpose classifier. To classify any database first, it is required to train the model. The proposed training algorithm used here is a Hybrid BP-GA. After successful training user can give unlabeled data to classify. 56 pp. Englisch. Nº de ref. del artículo: 9783848419937

Más información sobre este vendedor | Contactar al vendedor 5.

Amit Ganatra

Publicado por LAP Lambert Academic Publishing Mrz 2012 (2012)

ISBN 10: 3848419939 ISBN 13: 9783848419937

Nuevo
Tapa blanda

Cantidad disponible: 1

Vendedor: BuchWeltWeit Inh. Ludwig Meier e.K. (Bergisch Gladbach, Alemania)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 49,00
Convertir moneda
Gastos de envío: EUR 17,13
De Alemania a Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP Lambert Academic Publishing Mrz 2012, 2012. Taschenbuch. Condición: Neu. Neuware - In classifying large data set, efficiency and scalability are main issues. Advantages of neural networks include their high tolerance to noisy data, as well as their ability to classify patterns on which they have not been trained. Neural networks are a good choice for most classification and prediction tasks. The necessary complexity of neural networks is one of the most interesting problems in the research. One of the challenges in training MLP is in optimizing weight changes. Advances are introduced in traditional Back Propagation (BP) algorithm, to overcome its limitations. One method is to hybrid GA with BP to optimize weight changes.The objective here is to develop a data classification algorithm that will be used as a general-purpose classifier. To classify any database first, it is required to train the model. The proposed training algorithm used here is a Hybrid BP-GA. After successful training user can give unlabeled data to classify. 56 pp. Englisch. Nº de ref. del artículo: 9783848419937

Más información sobre este vendedor | Contactar al vendedor 6.

Ganatra, Amit

Publicado por LAP Lambert Academic Publishing (2013)

ISBN 10: 3659395870 ISBN 13: 9783659395871

Nuevo

Cantidad disponible: > 20

Vendedor: Books2Anywhere (Fairford, GLOS, Reino Unido)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 68,52
Convertir moneda
Gastos de envío: EUR 5,93
De Reino Unido a Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP Lambert Academic Publishing, 2013. 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. Nº de ref. del artículo: LQ-9783659395871

Más información sobre este vendedor | Contactar al vendedor 7.

Ganatra, Amit

Publicado por LAP Lambert Academic Publishing (2013)

ISBN 10: 3659395870 ISBN 13: 9783659395871

Nuevo

Cantidad disponible: > 20

Vendedor: Paperbackshop-US (Wood Dale, IL, Estados Unidos de America)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 74,48
Convertir moneda
Gastos de envío: GRATIS
A Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP Lambert Academic Publishing, 2013. PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: LQ-9783659395871

Más información sobre este vendedor | Contactar al vendedor 8.

Amit Ganatra

Publicado por LAP Lambert Academic Publishing, Germany (2012)

ISBN 10: 3848419939 ISBN 13: 9783848419937

Nuevo
Tapa blanda

Cantidad disponible: 1

Vendedor: The Book Depository EURO (London, Reino Unido)

Valoración del vendedor: Valoración 3 estrellas

Añadir al carrito
EUR 73,49
Convertir moneda
Gastos de envío: EUR 3,56
De Reino Unido a Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP Lambert Academic Publishing, Germany, 2012. Paperback. Condición: New. Aufl. Language: English . Brand New Book. In classifying large data set, efficiency and scalability are main issues. Advantages of neural networks include their high tolerance to noisy data, as well as their ability to classify patterns on which they have not been trained. Neural networks are a good choice for most classification and prediction tasks. The necessary complexity of neural networks is one of the most interesting problems in the research. One of the challenges in training MLP is in optimizing weight changes. Advances are introduced in traditional Back Propagation (BP) algorithm, to overcome its limitations. One method is to hybrid GA with BP to optimize weight changes.The objective here is to develop a data classification algorithm that will be used as a general-purpose classifier. To classify any database first, it is required to train the model. The proposed training algorithm used here is a Hybrid BP-GA. After successful training user can give unlabeled data to classify. Nº de ref. del artículo: KNV9783848419937

Más información sobre este vendedor | Contactar al vendedor 9.

Amit Ganatra

Publicado por LAP Lambert Academic Publishing Mrz 2012 (2012)

ISBN 10: 3848419939 ISBN 13: 9783848419937

Nuevo
Tapa blanda

Cantidad disponible: 1

Vendedor: AHA-BUCH GmbH (Einbeck, Alemania)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 49,00
Convertir moneda
Gastos de envío: EUR 34,50
De Alemania a Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP Lambert Academic Publishing Mrz 2012, 2012. Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Neuware - In classifying large data set, efficiency and scalability are main issues. Advantages of neural networks include their high tolerance to noisy data, as well as their ability to classify patterns on which they have not been trained. Neural networks are a good choice for most classification and prediction tasks. The necessary complexity of neural networks is one of the most interesting problems in the research. One of the challenges in training MLP is in optimizing weight changes. Advances are introduced in traditional Back Propagation (BP) algorithm, to overcome its limitations. One method is to hybrid GA with BP to optimize weight changes.The objective here is to develop a data classification algorithm that will be used as a general-purpose classifier. To classify any database first, it is required to train the model. The proposed training algorithm used here is a Hybrid BP-GA. After successful training user can give unlabeled data to classify. 56 pp. Englisch. Nº de ref. del artículo: 9783848419937

Más información sobre este vendedor | Contactar al vendedor 10.

Amit Ganatra

Publicado por LAP Lambert Academic Publishing Okt 2013 (2013)

ISBN 10: 3659395870 ISBN 13: 9783659395871

Nuevo
Tapa blanda

Cantidad disponible: 1

Vendedor: Rheinberg-Buch (Bergisch Gladbach, Alemania)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 71,90
Convertir moneda
Gastos de envío: EUR 17,13
De Alemania a Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP Lambert Academic Publishing Okt 2013, 2013. Taschenbuch. Condición: Neu. Neuware - Information fusion is becoming a major need in Data Mining. Typical applications of these techniques include data modeling (ensemble methods). The behavior of various classification algorithms differs based on accuracy and computational complexity. For some algorithms there may be a significant variation in the performance when some parameters are varied. In this research the behavior of the modified AdaBoost algorithm with NN as a base classifier and as a preprocessing step feature selection combined with the evaluation schemas (like subset evaluation, consistency based, correlation based, filter approach, wrapper approach etc.) are applied by varying the number of parameters. Predictive accuracy is substantially improved when combining multiple predictors. A novel idea of an Ensemble System applying Boosting to Neural Networks for High Dimensional Datasets. The method uses Genetic Algorithms (to select relevant features) for essential feature selection with various Evaluation Schemes. As Genetic Algorithms deal well with large solution spaces, tuning it to adjust as per the requirements of the ensemble, we can get optimum feature selection. Finally Boosting algorithm that finishe 200 pp. Englisch. Nº de ref. del artículo: 9783659395871

Más información sobre este vendedor | Contactar al vendedor 11.

Amit Ganatra

Publicado por LAP Lambert Academic Publishing Okt 2013 (2013)

ISBN 10: 3659395870 ISBN 13: 9783659395871

Nuevo
Tapa blanda

Cantidad disponible: 1

Vendedor: BuchWeltWeit Inh. Ludwig Meier e.K. (Bergisch Gladbach, Alemania)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 71,90
Convertir moneda
Gastos de envío: EUR 17,13
De Alemania a Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP Lambert Academic Publishing Okt 2013, 2013. Taschenbuch. Condición: Neu. Neuware - Information fusion is becoming a major need in Data Mining. Typical applications of these techniques include data modeling (ensemble methods). The behavior of various classification algorithms differs based on accuracy and computational complexity. For some algorithms there may be a significant variation in the performance when some parameters are varied. In this research the behavior of the modified AdaBoost algorithm with NN as a base classifier and as a preprocessing step feature selection combined with the evaluation schemas (like subset evaluation, consistency based, correlation based, filter approach, wrapper approach etc.) are applied by varying the number of parameters. Predictive accuracy is substantially improved when combining multiple predictors. A novel idea of an Ensemble System applying Boosting to Neural Networks for High Dimensional Datasets. The method uses Genetic Algorithms (to select relevant features) for essential feature selection with various Evaluation Schemes. As Genetic Algorithms deal well with large solution spaces, tuning it to adjust as per the requirements of the ensemble, we can get optimum feature selection. Finally Boosting algorithm that finishe 200 pp. Englisch. Nº de ref. del artículo: 9783659395871

Más información sobre este vendedor | Contactar al vendedor 12.

Amit Ganatra

Publicado por LAP LAMBERT Academic Publishing (2013)

ISBN 10: 3659395870 ISBN 13: 9783659395871

Nuevo
Tapa blanda

Cantidad disponible: > 20

Vendedor: California Books (MIAMI, FL, Estados Unidos de America)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 108,08
Convertir moneda
Gastos de envío: GRATIS
A Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP LAMBERT Academic Publishing, 2013. Condición: New. This book is printed on demand. Nº de ref. del artículo: I-9783659395871

Más información sobre este vendedor | Contactar al vendedor 13.

Amit Ganatra

Publicado por LAP Lambert Academic Publishing Okt 2013 (2013)

ISBN 10: 3659395870 ISBN 13: 9783659395871

Nuevo
Tapa blanda

Cantidad disponible: 1

Vendedor: AHA-BUCH GmbH (Einbeck, Alemania)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 71,90
Convertir moneda
Gastos de envío: EUR 34,50
De Alemania a Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP Lambert Academic Publishing Okt 2013, 2013. Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Neuware - Information fusion is becoming a major need in Data Mining. Typical applications of these techniques include data modeling (ensemble methods). The behavior of various classification algorithms differs based on accuracy and computational complexity. For some algorithms there may be a significant variation in the performance when some parameters are varied. In this research the behavior of the modified AdaBoost algorithm with NN as a base classifier and as a preprocessing step feature selection combined with the evaluation schemas (like subset evaluation, consistency based, correlation based, filter approach, wrapper approach etc.) are applied by varying the number of parameters. Predictive accuracy is substantially improved when combining multiple predictors. A novel idea of an Ensemble System applying Boosting to Neural Networks for High Dimensional Datasets. The method uses Genetic Algorithms (to select relevant features) for essential feature selection with various Evaluation Schemes. As Genetic Algorithms deal well with large solution spaces, tuning it to adjust as per the requirements of the ensemble, we can get optimum feature selection. Finally Boosting algorithm that finishe 200 pp. Englisch. Nº de ref. del artículo: 9783659395871

Más información sobre este vendedor | Contactar al vendedor 14.

Ganatra Amit

Publicado por LAP Lambert Academic Publishing, United States (2013)

ISBN 10: 3659395870 ISBN 13: 9783659395871

Nuevo
Tapa blanda

Cantidad disponible: 10

Vendedor: The Book Depository EURO (London, Reino Unido)

Valoración del vendedor: Valoración 3 estrellas

Añadir al carrito
EUR 104,59
Convertir moneda
Gastos de envío: EUR 3,56
De Reino Unido a Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP Lambert Academic Publishing, United States, 2013. Paperback. Condición: New. Language: English . Brand New Book ***** Print on Demand *****.Information fusion is becoming a major need in Data Mining. Typical applications of these techniques include data modeling (ensemble methods). The behavior of various classification algorithms differs based on accuracy and computational complexity. For some algorithms there may be a significant variation in the performance when some parameters are varied. In this research the behavior of the modified AdaBoost algorithm with NN as a base classifier and as a preprocessing step feature selection combined with the evaluation schemas (like subset evaluation, consistency based, correlation based, filter approach, wrapper approach etc.) are applied by varying the number of parameters. Predictive accuracy is substantially improved when combining multiple predictors. A novel idea of an Ensemble System applying Boosting to Neural Networks for High Dimensional Datasets. The method uses Genetic Algorithms (to select relevant features) for essential feature selection with various Evaluation Schemes. As Genetic Algorithms deal well with large solution spaces, tuning it to adjust as per the requirements of the ensemble, we can get optimum feature selection. Finally Boosting algorithm that finishe. Nº de ref. del artículo: AAV9783659395871

Más información sobre este vendedor | Contactar al vendedor 15.

Gaurang Panchal, Amit Ganatra

Publicado por LAP LAMBERT Academic Publishing (2012)

ISBN 10: 3848447479 ISBN 13: 9783848447473

Antiguo o usado
Tapa blanda

Cantidad disponible: 1

Vendedor: Ergodebooks (RICHMOND, TX, Estados Unidos de America)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 71,32
Convertir moneda
Gastos de envío: GRATIS
A Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP LAMBERT Academic Publishing, 2012. Paperback. Condición: Good. Nº de ref. del artículo: SONG3848447479

Más información sobre este vendedor | Contactar al vendedor 16.

Panchal, Gaurang; Ganatra, Amit

Publicado por LAP LAMBERT Academic Publishing (2012)

ISBN 10: 3848447479 ISBN 13: 9783848447473

Nuevo
Tapa blanda

Cantidad disponible: > 20

Vendedor: California Books (MIAMI, FL, Estados Unidos de America)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 81,06
Convertir moneda
Gastos de envío: GRATIS
A Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP LAMBERT Academic Publishing, 2012. Condición: New. This book is printed on demand. Nº de ref. del artículo: I-9783848447473

Más información sobre este vendedor | Contactar al vendedor 17.

Amit Ganatra, Gaurang Panchal, Chintan Gajjar

Publicado por LAP LAMBERT Academic Publishing (2012)

ISBN 10: 3848419939 ISBN 13: 9783848419937

Antiguo o usado
Tapa blanda

Cantidad disponible: 1

Vendedor: Ergodebooks (RICHMOND, TX, Estados Unidos de America)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 70,66
Convertir moneda
Gastos de envío: GRATIS
A Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP LAMBERT Academic Publishing, 2012. Paperback. Condición: Good. Nº de ref. del artículo: SONG3848419939

Más información sobre este vendedor | Contactar al vendedor 18.

Amit Ganatra; Gaurang Panchal; Chintan Gajjar

Publicado por LAP LAMBERT Academic Publishing (2012)

ISBN 10: 3848419939 ISBN 13: 9783848419937

Nuevo
Tapa blanda

Cantidad disponible: > 20

Vendedor: California Books (MIAMI, FL, Estados Unidos de America)

Valoración del vendedor: Valoración 5 estrellas

Añadir al carrito
EUR 81,06
Convertir moneda
Gastos de envío: GRATIS
A Estados Unidos de America
Destinos, gastos y plazos de envío

Descripción: LAP LAMBERT Academic Publishing, 2012. Condición: New. This book is printed on demand. Nº de ref. del artículo: I-9783848419937

Más información sobre este vendedor | Contactar al vendedor 19.

resultados (1 - 19) de 19