Description: Impact of Class Assignment on Multinomial Classification Using Multi-Valued Neurons by Julian Knaup Estimated delivery 3-12 business days Format Paperback Condition Brand New Description 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. Publisher Description 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. Author Biography Julian Knaup received his B. Sc. in Electrical Engineering and his M. Sc. in Information Technology from the University of Applied Sciences and Arts Ostwestfalen-Lippe. He is currently working on machine learning algorithms at the Institute Industrial IT and researching AI potentials in product creation. Details ISBN 3658389540 ISBN-13 9783658389543 Title Impact of Class Assignment on Multinomial Classification Using Multi-Valued Neurons Author Julian Knaup Format Paperback Year 2022 Pages 77 Edition 1st Publisher Springer Fachmedien Wiesbaden GE_Item_ID:137559391; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
Price: 114.39 USD
Location: Fairfield, Ohio
End Time: 2024-11-28T03:24:45.000Z
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ISBN-13: 9783658389543
Book Title: Impact of Class Assignment on Multinomial Classification Using Mu
Number of Pages: Xii, 77 Pages
Language: English
Publication Name: Impact of Class Assignment on Multinomial Classification Using Multi-Valued Neurons
Publisher: Springer Fachmedien Wiesbaden Gmbh
Publication Year: 2022
Subject: Intelligence (Ai) & Semantics, Probability & Statistics / General, General, Applied
Item Weight: 4.8 Oz
Type: Textbook
Subject Area: Mathematics, Computers
Author: Julian Knaup
Item Length: 8.3 in
Series: Bestmasters Ser.
Item Width: 5.8 in
Format: Trade Paperback