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Adhikari Ratnadip (author), Agrawal R. K. (author)

Published by LAP Lambert Academic Publishing 2013-01-29 (2013)

ISBN 10: 3659335088 ISBN 13: 9783659335082

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About this Item: LAP Lambert Academic Publishing 2013-01-29, 2013. paperback. Condition: New. Seller Inventory # 9783659335082

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Adhikari, Ratnadip / Agrawal, R. K.

ISBN 10: 3659335088 ISBN 13: 9783659335082

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About this Item: Condition: New. Publisher/Verlag: LAP Lambert Academic Publishing | Modeling and forecasting of time series data has fundamental importance in various practical domains. The aim of this book is to present a concise description of some popular time series forecasting models with their salient features. Three important classes of time series models, viz. stochastic, neural networks and support vector machines are studied together with their inherent forecasting strengths and weaknesses. The book also meticulously discusses about several basic issues related to time series analysis, such as stationarity, parsimony, overfitting, etc. Our study is enriched by presenting the empirical forecasting results, conducted on six real-world time series datasets. Five performance measures are used to evaluate the forecasting accuracies of different models as well as to compare the models. For each of the six time series datasets, we further show the obtained forecast diagram which graphically depicts the closeness between the original and predicted observations. | Format: Paperback | Language/Sprache: english | 76 pp. Seller Inventory # K9783659335082

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Adhikari, Ratnadip

Published by LAP Lambert Academic Publishing (2013)

ISBN 10: 3659335088 ISBN 13: 9783659335082

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About this Item: LAP Lambert Academic Publishing, 2013. PAP. Condition: New. New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # IQ-9783659335082

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Adhikari, Ratnadip

Published by LAP Lambert Academic Publishing (2013)

ISBN 10: 3659335088 ISBN 13: 9783659335082

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About this Item: LAP Lambert Academic Publishing, 2013. PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # LQ-9783659335082

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ISBN 10: 3659335088 ISBN 13: 9783659335082

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About this Item: Condition: New. Seller Inventory # ria9783659335082_ing

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Ratnadip Adhikari

Published by LAP Lambert Academic Publishing Jan 2015 (2015)

ISBN 10: 3659335088 ISBN 13: 9783659335082

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About this Item: LAP Lambert Academic Publishing Jan 2015, 2015. Taschenbuch. Condition: Neu. Neuware - Modeling and forecasting of time series data has fundamental importance in various practical domains. The aim of this book is to present a concise description of some popular time series forecasting models with their salient features. Three important classes of time series models, viz. stochastic, neural networks and support vector machines are studied together with their inherent forecasting strengths and weaknesses. The book also meticulously discusses about several basic issues related to time series analysis, such as stationarity, parsimony, overfitting, etc. Our study is enriched by presenting the empirical forecasting results, conducted on six real-world time series datasets. Five performance measures are used to evaluate the forecasting accuracies of different models as well as to compare the models. For each of the six time series datasets, we further show the obtained forecast diagram which graphically depicts the closeness between the original and predicted observations. 76 pp. Englisch. Seller Inventory # 9783659335082

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Ratnadip Adhikari

Published by LAP Lambert Academic Publishing Jan 2015 (2015)

ISBN 10: 3659335088 ISBN 13: 9783659335082

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About this Item: LAP Lambert Academic Publishing Jan 2015, 2015. Taschenbuch. Condition: Neu. Neuware - Modeling and forecasting of time series data has fundamental importance in various practical domains. The aim of this book is to present a concise description of some popular time series forecasting models with their salient features. Three important classes of time series models, viz. stochastic, neural networks and support vector machines are studied together with their inherent forecasting strengths and weaknesses. The book also meticulously discusses about several basic issues related to time series analysis, such as stationarity, parsimony, overfitting, etc. Our study is enriched by presenting the empirical forecasting results, conducted on six real-world time series datasets. Five performance measures are used to evaluate the forecasting accuracies of different models as well as to compare the models. For each of the six time series datasets, we further show the obtained forecast diagram which graphically depicts the closeness between the original and predicted observations. 76 pp. Englisch. Seller Inventory # 9783659335082

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R. K. Agrawal

Published by LAP LAMBERT Academic Publishing

ISBN 10: 3659335088 ISBN 13: 9783659335082

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About this Item: LAP LAMBERT Academic Publishing. Paperback. Condition: New. 76 pages. Dimensions: 8.7in. x 5.9in. x 0.2in.Modeling and forecasting of time series data has fundamental importance in various practical domains. The aim of this book is to present a concise description of some popular time series forecasting models with their salient features. Three important classes of time series models, viz. stochastic, neural networks and support vector machines are studied together with their inherent forecasting strengths and weaknesses. The book also meticulously discusses about several basic issues related to time series analysis, such as stationarity, parsimony, overfitting, etc. Our study is enriched by presenting the empirical forecasting results, conducted on six real-world time series datasets. Five performance measures are used to evaluate the forecasting accuracies of different models as well as to compare the models. For each of the six time series datasets, we further show the obtained forecast diagram which graphically depicts the closeness between the original and predicted observations. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Seller Inventory # 9783659335082

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Adhikari Ratnadip, Agrawal R K

Published by LAP Lambert Academic Publishing, United States (2015)

ISBN 10: 3659335088 ISBN 13: 9783659335082

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About this Item: LAP Lambert Academic Publishing, United States, 2015. Paperback. Condition: New. Language: English . Brand New Book ***** Print on Demand *****.Modeling and forecasting of time series data has fundamental importance in various practical domains. The aim of this book is to present a concise description of some popular time series forecasting models with their salient features. Three important classes of time series models, viz. stochastic, neural networks and support vector machines are studied together with their inherent forecasting strengths and weaknesses. The book also meticulously discusses about several basic issues related to time series analysis, such as stationarity, parsimony, overfitting, etc. Our study is enriched by presenting the empirical forecasting results, conducted on six real-world time series datasets. Five performance measures are used to evaluate the forecasting accuracies of different models as well as to compare the models. For each of the six time series datasets, we further show the obtained forecast diagram which graphically depicts the closeness between the original and predicted observations. Seller Inventory # AAV9783659335082

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Ratnadip Adhikari; R. K. Agrawal

Published by LAP LAMBERT Academic Publishing (2013)

ISBN 10: 3659335088 ISBN 13: 9783659335082

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About this Item: LAP LAMBERT Academic Publishing, 2013. Condition: New. book. Seller Inventory # M3659335088

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Ratnadip Adhikari

Published by LAP Lambert Academic Publishing Jan 2015 (2015)

ISBN 10: 3659335088 ISBN 13: 9783659335082

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About this Item: LAP Lambert Academic Publishing Jan 2015, 2015. Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Neuware - Modeling and forecasting of time series data has fundamental importance in various practical domains. The aim of this book is to present a concise description of some popular time series forecasting models with their salient features. Three important classes of time series models, viz. stochastic, neural networks and support vector machines are studied together with their inherent forecasting strengths and weaknesses. The book also meticulously discusses about several basic issues related to time series analysis, such as stationarity, parsimony, overfitting, etc. Our study is enriched by presenting the empirical forecasting results, conducted on six real-world time series datasets. Five performance measures are used to evaluate the forecasting accuracies of different models as well as to compare the models. For each of the six time series datasets, we further show the obtained forecast diagram which graphically depicts the closeness between the original and predicted observations. 76 pp. Englisch. Seller Inventory # 9783659335082

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Ratnadip Adhikari

Published by LAP LAMBERT Academic Publishing (2013)

ISBN 10: 3659335088 ISBN 13: 9783659335082

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About this Item: LAP LAMBERT Academic Publishing, 2013. Paperback. Condition: Good. Ships with Tracking Number! INTERNATIONAL WORLDWIDE Shipping available. May not contain Access Codes or Supplements. May be ex-library. Shipping & Handling by region. Buy with confidence, excellent customer service!. Seller Inventory # 3659335088

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Results (1 - 12) of 12