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- W3134269049 abstract "The goal of this research is to attain the epilepsy risk levels from Extracted features from EEG signals. This paper analyses a two-levelmethod of classification. At level one fuzzy method were endorsed to reach a multiple sub optimal solutions. Then the SVM and MRE classifiers were used to reach the singleton results. The Classifiers were compared by means of quality values. The SVM classifier accomplisher higher Quality Value of 23.02 when compared with other classifiers." @default.
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- W3134269049 date "2021-03-01" @default.
- W3134269049 modified "2023-09-26" @default.
- W3134269049 title "Analysis of Epilepsy Risk Levels from EEG Features through Support Vector Machine and Minimum Relative Entropy Model" @default.
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- W3134269049 doi "https://doi.org/10.1088/1757-899x/1084/1/012029" @default.
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