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Condition: As New. Unread book in perfect condition.
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Impact of Class Assignment on Multinomial Classification Using Multi-Valued Neurons (BestMasters)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Impact of Class Assignment on Multinomial Classification Using Multi-Valued Neurons
Published by Springer Vieweg 2022-08, 2022
ISBN 10: 3658389540 ISBN 13: 9783658389543
Language: English
PF. Condition: New.
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Impact of Class Assignment on Multinomial Classification Using Multi-valued Neurons
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Impact of Class Assignment on Multinomial Classification Using Multi-valued Neurons
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Impact Of Class Assignment On Multinomia
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New.
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Condition: New.
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Impact of Class Assignment on Multinomial Classification Using Multi-Valued Neurons
Published by Springer Fachmedien Wiesbaden, Springer Fachmedien Wiesbaden Aug 2022, 2022
ISBN 10: 3658389540 ISBN 13: 9783658389543
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -Multilayer neural networks based on multi-valued neurons (MLMVNs) have been proposed to combine the advantages of complex-valued neural networks with a plain derivative-free learning algorithm. In addition, multi-valued neurons (MVNs) offer a multi-valued threshold logic resulting in the ability to replace multiple conventional output neurons in classification tasks. Therefore, several classes can be assigned to one output neuron. This book introduces a novel approach to assign multiple classes to numerous MVNs in the output layer. It was found that classes that possess similarities should be allocated to the same neuron and arranged adjacent to each other on the unit circle. Since MLMVNs require input data located on the unit circle, two employed transformations are reevaluated. The min-max scaler utilizing the exponential function, and the 2D discrete Fourier transform restricting to the phase information for image recognition. The evaluation was performed on the Sensorless Drive Diagnosis dataset and the Fashion MNIST dataset.Springer Vieweg in Springer Science + Business Media, Abraham-Lincoln-Straße 46, 65189 Wiesbaden 92 pp. Englisch.
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Impact of Class Assignment on Multinomial Classification Using Multi-Valued Neurons
Published by Springer Fachmedien Wiesbaden, 2022
ISBN 10: 3658389540 ISBN 13: 9783658389543
Language: English
Taschenbuch. Condition: Neu. Impact of Class Assignment on Multinomial Classification Using Multi-Valued Neurons | Julian Knaup | Taschenbuch | xii | Englisch | 2022 | Springer Fachmedien Wiesbaden | EAN 9783658389543 | Verantwortliche Person für die EU: Springer Vieweg in Springer Science + Business Media, Abraham-Lincoln-Str. 46, 65189 Wiesbaden, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Impact of Class Assignment on Multinomial Classification Using Multi-Valued Neurons
Published by Springer Fachmedien Wiesbaden, 2022
ISBN 10: 3658389540 ISBN 13: 9783658389543
Language: English
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Multilayer neural networks based on multi-valued neurons (MLMVNs) have been proposed to combine the advantages of complex-valued neural networks with a plain derivative-free learning algorithm. In addition, multi-valued neurons (MVNs) offer a multi-valued threshold logic resulting in the ability to replace multiple conventional output neurons in classification tasks. Therefore, several classes can be assigned to one output neuron. This book introduces a novel approach to assign multiple classes to numerous MVNs in the output layer. It was found that classes that possess similarities should be allocated to the same neuron and arranged adjacent to each other on the unit circle. Since MLMVNs require input data located on the unit circle, two employed transformations are reevaluated. The min-max scaler utilizing the exponential function, and the 2D discrete Fourier transform restricting to the phase information for image recognition. The evaluation was performed on the Sensorless Drive Diagnosis dataset and the Fashion MNIST dataset.
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Impact of Class Assignment on Multinomial Classification Using Multi-Valued Neurons
Published by Springer Fachmedien Wiesbaden Aug 2022, 2022
ISBN 10: 3658389540 ISBN 13: 9783658389543
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Multilayer neural networks based on multi-valued neurons (MLMVNs) have been proposed to combine the advantages of complex-valued neural networks with a plain derivative-free learning algorithm. In addition, multi-valued neurons (MVNs) offer a multi-valued threshold logic resulting in the ability to replace multiple conventional output neurons in classification tasks. Therefore, several classes can be assigned to one output neuron. This book introduces a novel approach to assign multiple classes to numerous MVNs in the output layer. It was found that classes that possess similarities should be allocated to the same neuron and arranged adjacent to each other on the unit circle. Since MLMVNs require input data located on the unit circle, two employed transformations are reevaluated. The min-max scaler utilizing the exponential function, and the 2D discrete Fourier transform restricting to the phase information for image recognition. The evaluation was performed on the Sensorless Drive Diagnosis dataset and the Fashion MNIST dataset. 92 pp. Englisch.
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Impact of Class Assignment on Multinomial Classification Using Multi-Valued Neurons
Published by Springer, Berlin|Springer Fachmedien Wiesbaden|Springer Vieweg, 2022
ISBN 10: 3658389540 ISBN 13: 9783658389543
Language: English
Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Multilayer neural networks based on multi-valued neurons (MLMVNs) have been proposed to combine the advantages of complex-valued neural networks with a plain derivative-free learning algorithm. In addition, multi-valued neurons (MVNs) offer a multi-valued t.
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Condition: New. Print on Demand.
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Condition: New. PRINT ON DEMAND.
