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The results of experiments show that grid search-based SVM outperforms other optimized SVM approaches with 88.0% accuracy.
The experimental results for the product reviews show that the proposed hybrid model of SVM with PCA outperforms a single SVM in terms of classification accuracy and receiver-operating characteristic curve (ROC).
For the P300 data set (BCI competition III), for which a large number of trials is available, the sw-SVM proves to perform equivalently with respect to the ensemble SVM strategy that won the competition.
The results prove that a RBF kernel PCA?SVM technique is superior to PCA and conventional SVM (C-SVM) algorithms in classification serum SERS spectra.
Open accessJournal ArticleDOI
31 Aug 2018-IEEE Access
78 Citations
The proposed CSP\AM-BA-SVM transcends the traditional CSP\SVM approach and other existing studies.
The experiment results show that MSFLA-SVM achieves a much higher fault classification rate than BPNN, ACROA-SVM, and SFLA-SVM.
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.
The results prove that RBF SVM models are superior to PCA algorithm in classification serum SERS spectra.