Automatic Healthcare Diagnosis and Prediction Assessment based on AI Multi-Classification Algorithm

Author(s):  
Safiah Endargiri ◽  
Kaouther Laabidi
2011 ◽  
Vol 268-270 ◽  
pp. 1115-1120
Author(s):  
De Qian Xue

Semi-supervised Support Vector Data Description multi-classification algorithm is presented, in order to solve less labeled data learning, difficulties in the implementation and poor results of semi-supervised multi-classification, which full use the distribution of information in of non-target samples. S3VDD-MC algorithm defines the degree of membership of non-target samples, in order to get the non-target samples’ accepted labels or refused labels, on this basis, several super-spheres constructed, a k-classification problem is transformed into k SVDDs problem. Finally, the simulation results verify the effectiveness of the algorithm.


2011 ◽  
Vol 55-57 ◽  
pp. 1803-1806 ◽  
Author(s):  
Bao Ling Liu

The paper presented the improved “one to many” classification algorithm in the basis of analyzing the shortcoming of the two traditional multi-classification algorithm, and established multi-fault classifier based on SVM to class the turbine typical faults. The results shows that the classifier may get satisfied effect.


2022 ◽  
Vol 74 ◽  
pp. 101677
Author(s):  
Jun Li ◽  
Qiyan Dou ◽  
Haima Yang ◽  
Jin Liu ◽  
Le Fu ◽  
...  

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