Improved neural network for SVM learning
Tóm tắt
The recurrent network of Xia et al. (1996) was proposed for solving quadratic programming problems and was recently adapted to support vector machine (SVM) learning by Tan et al. (2000). We show that this formulation contains some unnecessary circuits which, furthermore, can fail to provide the correct value of one of the SVM parameters and suggest how to avoid these drawbacks.
Từ khóa
#Neural networks #Support vector machines #Support vector machine classification #Quadratic programming #Machine learning #Circuits #Hardware #Proposals #Very large scale integration #Differential equationsTài liệu tham khảo
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