Sentence examples for support a recursive from inspiring English sources

EHR system data models do not usually support a recursive duplication of entry fields during documentation.

Results: We developed a recursive support vector machine (R-SVM) algorithm to select important genes/biomarkers for the classification of noisy data.

The methods aimed for binary class data use a recursive support vector machine (R-SVM) algorithm to analyze noisy high-throughput proteomics and microarray data (Zhang et al., 2006) and a method that computes the feature ranking score from statistical analysis of weight vectors of multiple linear SVMs trained on subsamples of the original training data (Duan et al., 2005).

To this aim, we here used gene expression features and drug sensitivity data in Cancer Cell Line Encyclopedia (CCLE) to build a predictor based on Support Vector Machine (SVM) and a recursive feature selection tool.

Moreover, the Taylor expansion of the optimal support points can be determined efficiently by a recursive procedure.

Additionally, we proposed a Support Vector based Recursive Feature Addition (SVRFA) scheme for SNP-disease association analysis.

A Support Vector based Recursive Feature Addition (SVRFA) scheme is also proposed to aid SNP-disease association analysis.

Additionally, we have proposed a Support Vector based Recursive Feature Addition (SVRFA) scheme in SNP-disease association analysis.

We developed a Support Vector Machine Recursive Feature Elimination(SVM-RFE) method [ 6] based on Cross-Validation (CV) (SVM-RFE-CV) to eliminate features for breast cancer from peripheral blood.

For example, SVMSEQ (Wu and Zhang, 2008) uses support vector machines for contact prediction; NNcon (Tegge et al., 2009) uses a recursive neural network; SVMcon (Cheng and Baldi, 2007) also uses support vector machines plus features derived from sequence homologs; Distill (Baú et al., 2006) uses a 2D recursive neural network.

In our study, features are selected using a recursive feature selection namely SVM-RFE (Support Vector Machine Recursive Feature Elimination).