Using Duo Output Neural Network to solve binary classification problems
This paper proposes an approach to solve binary classification problems using Duo Output Neural Network (DONN). DONN is a neural network trained to predict a pair of complementary outputs which are the truth and falsity values. In this paper, outputs obtained from two DONNs are aggregated and used t...
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th-mahidol.289872018-09-24T15:56:40Z Using Duo Output Neural Network to solve binary classification problems Pawalai Kraipeerapun Somkid Amornsamankul Ramkhamhaeng University Mahidol University South Carolina Commission on Higher Education Computer Science This paper proposes an approach to solve binary classification problems using Duo Output Neural Network (DONN). DONN is a neural network trained to predict a pair of complementary outputs which are the truth and falsity values. In this paper, outputs obtained from two DONNs are aggregated and used to predict the classification result. The first DONN is trained to predict a pair of truth and falsity values. The second DONN is trained to predict a pair of falsity and truth values. The target outputs used to train the second network are organized in reverse order of the first network. The proposed approach has been tested with three benchmarking UCI data sets, which are ionosphere, pima, and liver. It is found that the proposed techniques improve the performance as compared to feedforward backprogation neural network and complementary neural network. 2018-09-24T08:56:40Z 2018-09-24T08:56:40Z 2010-12-01 Conference Paper International Conference on Applied Computer Science - Proceedings. (2010), 286-290 17924863 2-s2.0-79958735976 https://repository.li.mahidol.ac.th/handle/123456789/28987 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79958735976&origin=inward |
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Computer Science Pawalai Kraipeerapun Somkid Amornsamankul Using Duo Output Neural Network to solve binary classification problems |
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This paper proposes an approach to solve binary classification problems using Duo Output Neural Network (DONN). DONN is a neural network trained to predict a pair of complementary outputs which are the truth and falsity values. In this paper, outputs obtained from two DONNs are aggregated and used to predict the classification result. The first DONN is trained to predict a pair of truth and falsity values. The second DONN is trained to predict a pair of falsity and truth values. The target outputs used to train the second network are organized in reverse order of the first network. The proposed approach has been tested with three benchmarking UCI data sets, which are ionosphere, pima, and liver. It is found that the proposed techniques improve the performance as compared to feedforward backprogation neural network and complementary neural network. |
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Ramkhamhaeng University |
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Ramkhamhaeng University Pawalai Kraipeerapun Somkid Amornsamankul |
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Conference or Workshop Item |
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Pawalai Kraipeerapun Somkid Amornsamankul |
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Pawalai Kraipeerapun |
title |
Using Duo Output Neural Network to solve binary classification problems |
title_short |
Using Duo Output Neural Network to solve binary classification problems |
title_full |
Using Duo Output Neural Network to solve binary classification problems |
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Using Duo Output Neural Network to solve binary classification problems |
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Using Duo Output Neural Network to solve binary classification problems |
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using duo output neural network to solve binary classification problems |
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2018 |
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https://repository.li.mahidol.ac.th/handle/123456789/28987 |
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