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Multi-class classification SVM methods
Zhao Di
problem is multi-classification. We need to solve the multiclassification problem on a dichotomy basis.
On methods for improving the accuracy of multi-class classification on imbalanced data
Sevastianov L.A., Shchetinin E.Yu.
machine learning methods to eliminate class imbalance in data in order to improve accuracy in multi-class
On improving the accuracy of the classification on imbalanced classes with machine learning
Shchetinin E.Y., Sevastianov L.A., Kulyabov D.S., Ayrjan E.A.
machine learning methods to eliminate class imbalance in data in order to improve accuracy in multi-class
On methods for improving the accuracy of multi-class classification on unbalanced data
Sevastianov L.A., Shchetinin E.Y.
machine learning methods to eliminate class imbalance in data in order to improve accuracy in multi-class
Multi-agent system for сontrol sound information
Visniakou, U. A., Вишняков, В. А., Shaya, B. H., Сайя, Б. Х.
The multi-agent system for monitoring sound information (MAMS) in the environment is a set
Analysis of support vector machine based decoding algorithm for bose-chaudhuri-hocquenghem codes
Galchenko, M. I., Ramanouski, Y. Y., Spichekova, N. V.
are applied to transmit the message over the channel. Bose-Chaudhuri-Hocquenghem (BCH) is a class of codes
An ensemble method based on rotation calibrated least squares support vector machine for multi-source data classification
Khosravi I., Razoumny V.Y., Afkoueieh J.H., Alavipanah S.K.
This paper proposed an extended rotation-based ensemble method for the classification of a multi
Operations of classification thinking in students working on verbal tasks
Kurbanova A., Salikhova N.
of classes as isolated, but they rarely use them as a means of solving classification problems on the verbal
Operations of classification thinking in students working on verbal tasks
Kurbanova A., Salikhova N.
of classes as isolated, but they rarely use them as a means of solving classification problems on the verbal
Minimax Modifications of Linear Discriminant Analysis for Classification with Rare Classes
Bratanova K., Kareev I., Salimov R.
© 2020 IEEE. We consider the problem of classification for imbalanced samples with rare classes. A

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