Sentence examples for multivariate classification algorithms from inspiring English sources
We applied and contrasted the following multivariate classification algorithms to predict HER2, ER, and PR IHC positivity separately.
Multivariate classification algorithms distinguished breast cancer patients from the normal population with high accuracy (91.8% with random forest, 91.5% with support vector machine, 87.6% with linear discriminant analysis).
Multivariate classification algorithms were used to find discriminating biomarkers and validated with another independent population of 90 breast cancer and 79 healthy controls.
Such assays, which include MammaPrint [ 3], OncotypeDx [ 4], PAM50 Breast Cancer Intrinsic Subtype Classifier [ 5], MapQuant Dx [ 6] and Theros Breast Cancer Index [ 7], are implemented by providing multiple gene expression measurements obtained from tissue samples to multivariate classification algorithms.
The values of markers were transformed into log values before analysis using a multivariate classification algorithm.
SVM is a supervised multivariate classification algorithm based on pattern recognition.
To allow distinction between first-degree relatives and patients with RA, a multivariate classification algorithm termed the Random Forest method was used.
After 13 proteins were selected as candidate biomarkers, multivariate classification analyses were used to identify algorithms for diagnostic biomarker combinations.
Here, in addition to the traditional method of group comparisons on individual measures, we also used support vector machine (SVM) algorithms, a supervised multivariate classification method, which has proved useful, although not perfect, at distinguishing clinical groups using neuroimaging data [Ecker et al., 2010 ].
Recursive partitioning is a type of multivariate analysis whose purpose is the construction of classification algorithms, and it is especially useful when there are a large number of predictive variables with complex relationships with the event.
For the second category, the development of classifier design, we make a survey on various classification algorithms used in existing blind detection methods, and detail the algorithms behind several classifiers based on multivariate regression analysis, OC-SVM, ANN, CIS and Hyper-geometric structure.
