Transductive inference estimates classification function at samples within the test data using information from both the training and the test data set.
In this paper, a new algorithm of transductive support vector machine is proposed to improve Joachims' transductive SVM to handle various data distributions.
Simulated annealing heuristic is used to solve the combinatorial optimization problem of TSVM, in order to avoid the problems of having to estimate the ratio of ...
Feb 7, 2022 · In this paper, we propose a safe TSVM (STSVM) based on the infinitesimal annealing algorithm. In the training of TSVM, we adopt the infinitesimal annealing and ...
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with simulated annealing (TSVM-SA) is designed to implement effective transductive inferencein support vector learning. The idea of simulated annealing ...
The infinitesimal annealing algorithm is a novel training method of TSVM which can alleviate the impact of the combinatorial and non-convex natures in TSVM and ...
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In this paper, we propose a safe TSVM (STSVM) based on the infinitesimal annealing algorithm. In the training of TSVM, we adopt the infinitesimal annealing and ...
In the training of TSVM, we adopt the infinitesimal annealing and path following technology to approximate the step size of simulated annealing to balance the ...
In the training of TSVM, we adopt the infinitesimal annealing and path following technology to approximate the step size of simulated annealing to balance the ...
Jul 10, 2017 · When solving optimization problem in the improved deduction support vector machine, simulated annealing algorithm introduced in last section is ...
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