Classification of Data from Electronic Nose Using Gradient Tree Boosting Algorithm

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 thi...

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Bibliographic Details
Main Authors: Yuan Luo, Wenbin Ye, Xiaojin Zhao, Xiaofang Pan, Yuan Cao
Format: Article
Language:English
Published: MDPI AG 2017-10-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/17/10/2376
Description
Summary: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.
ISSN:1424-8220