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Sensors 2017, 17(10), 2376; doi:10.3390/s17102376

Classification of Data from Electronic Nose Using Gradient Tree Boosting Algorithm

1
School of Electronic Science and Technology, Shenzhen University, Shenzhen 518060, China
2
Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
3
School of Information Engineering, Shenzhen University, Shenzhen 518060, China
*
Author to whom correspondence should be addressed.
Received: 16 August 2017 / Revised: 2 October 2017 / Accepted: 17 October 2017 / Published: 18 October 2017
(This article belongs to the Special Issue Artificial Olfaction and Taste)
View Full-Text   |   Download PDF [465 KB, uploaded 18 October 2017]   |  

Abstract

In this paper, an approach that can fast classify the data from the electronic nose is presented. In this approach the gradient tree boosting algorithm is used to classify the gas data and the experiment results show that the proposed gradient tree boosting algorithm achieved high performance on this classification problem, outperforming other algorithms as comparison. In addition, electronic nose we used only requires a few seconds of data after the gas reaction begins. Therefore, the proposed approach can realize a fast recognition of gas, as it does not need to wait for the gas reaction to reach steady state. View Full-Text
Keywords: electronic nose; gas sensors; gradient tree boosting; fast recognition electronic nose; gas sensors; gradient tree boosting; fast recognition
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Luo, Y.; Ye, W.; Zhao, X.; Pan, X.; Cao, Y. Classification of Data from Electronic Nose Using Gradient Tree Boosting Algorithm. Sensors 2017, 17, 2376.

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