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Text classification using convolutional neural network committee training

Электронный архив ТПУ

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Поле Значение
 
Заглавие Text classification using convolutional neural network committee training
 
Автор Krivosheev, N. A.
Spitsyn, Vladimir Grigorievich
 
Тематика convolutional neural networks
Bagging
text classification
text database "The 20 Newsgroup"
сверточные нейронные сети
текстовые данные
базы данных
текстовая информация
 
Описание The method of classification of textual information based on the apparatus of convolutional neural networks is considered. The word-by-word text conversion into dense vectors is considered. Testing was conducted on the text data of the sample “The 20 Newsgroups”, this sample contains texts distributed in 20 classes. The accuracy, the best of the convolutional neural network used in this work, on the test sample was ~ 74%. The accuracy of voting of neural networks using the Bagging algorithm was ~ 81.5%. Based on the review of similar solutions, a comparison was made with the following text classification algorithms: using the support vector machine (SVM, 82.84%), naive bayes classifier (81%), k nearest neighbor algorithm (75.93%), a bag of words.
 
Дата 2020-01-23T09:13:04Z
2020-01-23T09:13:04Z
2019
 
Тип Conference Paper
Published version (info:eu-repo/semantics/publishedVersion)
Conference paper (info:eu-repo/semantics/conferencePaper)
 
Идентификатор Krivosheev N. A. Text classification using convolutional neural network committee training / N. A. Krivosheev, V. G. Spitsyn // 14th International Forum on Strategic Technology (IFOST-2019), October 14-17, 2019, Tomsk, Russia : [proceedings]. — Tomsk : TPU Publishing House, 2019. — [С. 274-277].
http://earchive.tpu.ru/handle/11683/57468
 
Язык en
 
Связанные ресурсы 14th International Forum on Strategic Technology (IFOST-2019), October 14-17, 2019, Tomsk, Russia : [proceedings]. — Tomsk, 2019.
 
Права Open access (info:eu-repo/semantics/openAccess)