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Finally, PO-aligned features are compared for classification.
Principal component analysis (PCA) and independent component analysis (ICA) are investigated for feature extraction and compared for classification results using SVM.
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Mortality according to AKI occurence was compared for each classification.
In this work, three machine learning approaches, SVM, CRF, and LSTM are compared for style classification.
Features of physical parameters [k1, kc] were compared for their classification performance before and after VTL estimation.
Studied parameters were compared for various classification methods and over-time evaluation techniques (paired samples) by applying the sign test, Wilcoxon signed-rank test, and Friedman test.
Linear discriminant analysis and support vector machine classifiers were compared for their classification performances after a standard or a Gaussian kernel principal component analysis.
Discrimination was assessed by the c-statistic for survival data 18 19 and other models were compared, for risk classification, with the basic model using the continuous form of the net reclassification index (NRI) for 10-year risk of CHD.
In this paper, seven regression algorithms have been applied and compared for PQ disturbances classification.
When the empirical and FIA classifications were compared for FIA plots across the U.S., there were necessarily some similarities to the eastern U.S. comparison because eastern U.S. plots were included in the full set of U.S. plots.
Because most of the processes related to P or B at environmentally relevant concentrations are driven by first-order or pseudo-first-order kinetics and thus are lognormally distributed, geometric mean values are the most appropriate for comparing triggers for classification and were used in this assessment.
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