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Multivariate classification models were applied to recorded data in 30-minute epochs of time to predict crises between 15 and 360 minutes in the future.
In order to demonstrate that our results are independent of a particular methodology we developed and compared multivariate classification models obtained using two independent procedures.
Long-term survival of breast cancer patients has been successfully predicted from breast cancer tissue using multivariate classification models [ 15].
The multivariate classification models chosen for this study were K-nearest neighbors (KNN) and support vector machine (SVM).
Partial least-squares discriminant analysis (PLS-DA) was utilized to build multivariate classification models to discern high virulence RNA binding to the substrate.
The infrared spectra could be correlated to specific flavour notes, such as fermented, sour, and unclean, and differentiated using multivariate classification models.
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The factorization approach successfully de-correlated epigenetic marks, which resulted in an interpretable multivariate classification model.
Pd and Ps scores could then be generated in the field by web or phone-based applications running multivariate regression classification models.
9 To discern key mechanisms of the invasive inflammatory disease endometriosis, for example, experimental measurements of cytokines, growth factors, and protease activities from human patient peritoneal fluid samples have been used in multivariate classification and network models.
Statistical relations between road characteristics and speed indicators were explored using multivariate classification methods and regression models.
The eight predictors were then evaluated simultaneously using a multivariate classification and regression tree (CART) model, which is a recursive binary partitioning model.
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