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Machine Learning Techniques Adaptive (36 results)
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Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series)
Seller: Wonder Book, Frederick, MD, U.S.A.
Seller rating 5 out of 5 stars
Condition: Very Good. Very Good condition. A copy that may have a few cosmetic defects. May also contain light spine creasing or a few markings such as an owner's name, short gifter's inscription or light stamp. NOT AVAILABLE FOR SHIPMENT OUTSIDE OF THE UNITED STATES.
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Condition: very_good. Book is in very good condition and may include minimal underlining highlighting. The book can also include "From the library of" labels. May not contain miscellaneous items toys, dvds, etc. . We offer 100% money back guarantee and 24 7 customer service.
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Hardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Hardcover. Condition: Acceptable. Connecting readers with great books since 1972. Used textbooks may not include companion materials such as access codes, etc. May have condition issues including wear and notes/highlighting. We ship orders daily and Customer Service is our top priority!
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Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series)
Language: English
Published by The MIT Press (edition 1), 2009
ISBN 10: 0262013193 ISBN 13: 9780262013192
Hardcover. Condition: Good. 1. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.
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Condition: very_good. The book does not look new and has been read but is in excellent condition. The cover and dust jacket if applicable may have very minimal or no wear. There are no missing or damaged pages, no creases or tears, and no writing, highlighting or underlining of text. May have an author autograph or inscription from author. May have very minimal identifying marks inside cover. May have pale yellow pages. May have minimal light marks on page edges or a remainder mark. Fast Shipping, safe and secure mailers. Stock photo used.
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Knowledge Graphs: Fundamentals, Techniques, and Applications (Adaptive Computation and Machine Learning)
Seller: WorldofBooks, Goring-By-Sea, WS, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
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hardcover. Condition: Good. 1st Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
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Knowledge Graphs: Fundamentals, Techniques, and Applications (Adaptive Computation and Machine Learning series)
Language: English
Published by The MIT Press Bookstore, 2021
ISBN 10: 0262045095 ISBN 13: 9780262045094
Condition: New.
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Knowledge Graphs: Fundamentals, Techniques, and Applications (Adaptive Computation and Machine Learning series)
Language: English
Published by The MIT Press Bookstore, 2021
ISBN 10: 0262045095 ISBN 13: 9780262045094
Condition: New.
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Machine Learning Classification of Epileptic Seizures Based on EEG: using Third-Ordered Cumulants and Adaptive Fractal Analysis Techniques
Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206152960 ISBN 13: 9786206152965
Condition: New.
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Knowledge Graphs: Fundamentals, Techniques, and Applications (Adaptive Computation and Machine Learning series)
Language: English
Published by The MIT Press Bookstore, 2021
ISBN 10: 0262045095 ISBN 13: 9780262045094
Condition: New.
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hardcover. Condition: Very Good. Very Good Condition - May show some limited signs of wear and may have a remainder mark. Pages and dust cover are intact and not marred by notes or highlighting.
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Knowledge Graphs: Fundamentals, Techniques, and Applications (Adaptive Computation and Machine Learning series)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 67.41
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Machine Learning Classification of Epileptic Seizures Based on EEG: using Third-Ordered Cumulants and Adaptive Fractal Analysis Techniques
Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206152960 ISBN 13: 9786206152965
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 69.41
US$ 16.06 shipping
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US$ 63.05
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Ships from United Kingdom to U.S.A.Quantity: 2 available
Add to baskethardcover. Condition: New.
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Condition: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
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Machine Learning Techniques For Adaptive Multimedia Retrieval: Technologies Applications And Perspectives (Premier Reference Source)
Language: English
Published by Information Science Reference, 2010
ISBN 10: 161692859X ISBN 13: 9781616928599
Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Machine Learning Classification of Epileptic Seizures Based on EEG | using Third-Ordered Cumulants and Adaptive Fractal Analysis Techniques
Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206152960 ISBN 13: 9786206152965
Taschenbuch. Condition: Neu. Machine Learning Classification of Epileptic Seizures Based on EEG | using Third-Ordered Cumulants and Adaptive Fractal Analysis Techniques | Buchanna Gajula | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206152965 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 147.17
US$ 16.06 shipping
Ships from United Kingdom to U.S.A.Quantity: 4 available
Add to basketCondition: New. In.
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Machine Learning Classification of Epileptic Seizures Based on EEG: using Third-Ordered Cumulants and Adaptive Fractal Analysis Techniques
Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206152960 ISBN 13: 9786206152965
US$ 143.64
US$ 33.52 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketpaperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Machine Learning Techniques for Adaptive Multimedia Retrieval: Technologies Applications and Perspectives
Language: English
Published by Information Science Reference, 2010
ISBN 10: 161692859X ISBN 13: 9781616928599
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 205.26
US$ 16.06 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
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US$ 198.89
US$ 33.52 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketHardcover. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Hardcover. Condition: Sehr gut. Gebraucht - Sehr gut Sg - leichte Beschädigungen oder Verschmutzungen, ungelesenes Mängelexemplar, gestempelt - A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.Most tasks require a person or an automated system to reason to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality. Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.
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International EditionUS$ 271.13
US$ 5.35 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketCondition: New. Brand New! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Machine Learning Classification of Epileptic Seizures Based on EEG : using Third-Ordered Cumulants and Adaptive Fractal Analysis Techniques
Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206152960 ISBN 13: 9786206152965
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Machine Learning Classification of Epileptic Seizures Based on Electroencephalogram using Third-Ordered Cumulants and Adaptive Fractal Analysis Techniques1 IntroductionEpilepsy is one of the serious neurological diseases in the world. Indeed, early detection of epileptic seizures will extend the life span of epileptic patients. In this regard, a lot of efforts has been done to predict epileptic seizures based on electroencephalography (EEG) signals. In literature, there are many feature-based seizure classification methods quoted. No method is proved perfectly in capturing a standard set of features with the dynamics of signals. It is a common neurological disorder caused by the abnormally rapid release of brain nerve cells that is characterized by seizures. The scalp or intracranial Electroencephalogram (EEG) signals obtained in the clinic typically exhibit characteristics such as chaos, nonlinearity, etc.Deep neural networks have made significant advances in the field of machine learning during the last era. The model can learn effective representations from raw data in both supervised and unsupervised contexts by creating a hierarchical or 'deep' structure.
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Machine Learning Techniques for Adaptive Multimedia Retrieval
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 4 out of 5 stars
US$ 212.90
US$ 10.23 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHRD. 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.
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HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
