Ensemble as a Piecewise Linear Classifier

2006 ◽  
Author(s):  
Pitoyo Hartono ◽  
Shuji Hashimoto
Keyword(s):  
Piecewise Linear ◽  
Linear Classifier

scholarly journals An incremental piecewise linear classifier based on polyhedral conic separation

2014 ◽  
Vol 101 (1-3) ◽  
pp. 397-413 ◽  
Author(s):  
Gurkan Ozturk ◽  
Adil M. Bagirov ◽  
Refail Kasimbeyli
Keyword(s):  
Piecewise Linear ◽  
Linear Classifier

Comparison of a neural network and a piecewise linear classifier

1991 ◽  
Vol 12 (11) ◽  
pp. 649-655 ◽  
Author(s):  
Zhen-Ping Lo ◽  
Behnam Bavarian
Keyword(s):  
Neural Network ◽  
Piecewise Linear ◽  
Linear Classifier

A novel piecewise linear classifier based on polyhedral conic and max–min separabilities

Top ◽  
2011 ◽  
Vol 21 (1) ◽  
pp. 3-24 ◽  
Author(s):  
Adil M. Bagirov ◽  
Julien Ugon ◽  
Dean Webb ◽  
Gurkan Ozturk ◽  
Refail Kasimbeyli
Keyword(s):  
Piecewise Linear ◽  
Linear Classifier

Multiconlitron: A General Piecewise Linear Classifier

2011 ◽  
Vol 22 (2) ◽  
pp. 276-289 ◽  
Author(s):  
Li Yujian ◽  
Liu Bo ◽  
Yang Xinwu ◽  
Fu Yaozong ◽  
Li Houjun
Keyword(s):  
Piecewise Linear ◽  
Linear Classifier

scholarly journals Multimedia Digital Signal Processing of Infrared Chemical Remote Sensing Based on Piecewise Linear Discriminant Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Meitao Gong
Keyword(s):  
Remote Sensing ◽  
Piecewise Linear ◽  
Digital Signal ◽  
Signal Recovery ◽  
Linear Discriminant ◽  
Linear Classifier ◽  
Separate Line ◽  
Relaxation Factors ◽  
Constrained Conditions ◽  
Better Than

According to the basic principle of piecewise linear classifier and its application in the field of infrared chemical remote sensing monitoring, the characteristics of unilateral piecewise linear classifier applied to the infrared spectrum identification of chemical agents are studied. With the characteristic of separate transmission, the characteristic recovery with the total observed deviation is used for the model. The relaxation factors are used to replace the constrained conditions that cannot be optimized into constrained separate line segment calculation conditions. Experiments show that the result of signal recovery is better than traditional Wiener filtering and Richardson–Lucy methods.

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