A procedure of linear discrimination analysis with detected sparsity structure for high-dimensional multi-class classification

2020 ◽  
Vol 179 ◽  
pp. 104641 ◽  
Author(s):  
Shan Luo ◽  
Zehua Chen
The Analyst ◽  
2016 ◽  
Vol 141 (11) ◽  
pp. 3242-3245 ◽  
Author(s):  
Jiatao Wu ◽  
Chunyan Tan ◽  
Zhifang Chen ◽  
Yu Zong Chen ◽  
Ying Tan ◽  
...  

A sensor array consisting of six conjugated polyelectrolytes was constructed to discriminate between nine nitroaromatics by linear discrimination analysis.


2012 ◽  
Vol 518-523 ◽  
pp. 4620-4625
Author(s):  
Xing Zhang Chen ◽  
Yong You ◽  
Jin Feng Liu

In this paper, we firstly defined the potential debris flow gully. And then using the data of different gullies in Wenchuan earthquake hit areas, we built a discrimination model of potential debris flow gully by Fisher Linear Discrimination Analysis method. Finally, the model was used to discriminate the gullies in Jinxihe catchment, in Anxian County. Potential debris flow gully is a kind of special gully which is in a special evolution phase of the gully when the gully has the happening possibilities of debris flow but no debris flow records. Because potential debris flow can often pose more serious disasters, discrimination of potential debris flow gully is important for disaster prevention and mitigation. To build discrimination model of potential debris flow gully, a database of different gullies in quake-hit areas was established and six discrimination indices were selected based on cause analysis of debris flow. Using the database and the six discrimination indices, we built the discrimination model by Fisher Linear Discrimination Analysis method. The discrimination model was used to discriminate the gullies in Jinxihe catchment. Discrimination results showed that the discrimination model was effective and feasible in discriminating potential debris flow gullies, but it still needs further revised and perfected.


2011 ◽  
Vol 191 (3) ◽  
pp. 174-181 ◽  
Author(s):  
Tomas Kasparek ◽  
Carlos Eduardo Thomaz ◽  
Joao Ricardo Sato ◽  
Daniel Schwarz ◽  
Eva Janousova ◽  
...  

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