svms using libsvm function Search Results


weka-knime libsvm node  (KNIME GmbH)
90
KNIME GmbH weka-knime libsvm node
Accuracy, cohen’s κ, TPR and TNR values based for the all ML tools and using either 5-fold cross validation or 20% testing set for prediction people with T2DM from people without T2DM.
Weka Knime Libsvm Node, supplied by KNIME GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/weka-knime libsvm node/product/KNIME GmbH
Average 90 stars, based on 1 article reviews
weka-knime libsvm node - by Bioz Stars, 2026-05
90/100 stars
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svm toolbox function libsvm  (MathWorks Inc)
96
MathWorks Inc svm toolbox function libsvm
Accuracy, cohen’s κ, TPR and TNR values based for the all ML tools and using either 5-fold cross validation or 20% testing set for prediction people with T2DM from people without T2DM.
Svm Toolbox Function Libsvm, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/svm toolbox function libsvm/product/MathWorks Inc
Average 96 stars, based on 1 article reviews
svm toolbox function libsvm - by Bioz Stars, 2026-05
96/100 stars
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svm models  (CH Instruments)
90
CH Instruments svm models
Accuracy, cohen’s κ, TPR and TNR values based for the all ML tools and using either 5-fold cross validation or 20% testing set for prediction people with T2DM from people without T2DM.
Svm Models, supplied by CH Instruments, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/svm models/product/CH Instruments
Average 90 stars, based on 1 article reviews
svm models - by Bioz Stars, 2026-05
90/100 stars
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svms libsvm package  (Emphron Informatics)
90
Emphron Informatics svms libsvm package
Accuracy, cohen’s κ, TPR and TNR values based for the all ML tools and using either 5-fold cross validation or 20% testing set for prediction people with T2DM from people without T2DM.
Svms Libsvm Package, supplied by Emphron Informatics, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/svms libsvm package/product/Emphron Informatics
Average 90 stars, based on 1 article reviews
svms libsvm package - by Bioz Stars, 2026-05
90/100 stars
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Image Search Results


Accuracy, cohen’s κ, TPR and TNR values based for the all ML tools and using either 5-fold cross validation or 20% testing set for prediction people with T2DM from people without T2DM.

Journal: PLoS ONE

Article Title: Investigating the association of CD36 gene polymorphisms (rs1761667 and rs1527483) with T2DM and dyslipidemia: Statistical analysis, machine learning based prediction, and meta-analysis

doi: 10.1371/journal.pone.0257857

Figure Lengend Snippet: Accuracy, cohen’s κ, TPR and TNR values based for the all ML tools and using either 5-fold cross validation or 20% testing set for prediction people with T2DM from people without T2DM.

Article Snippet: In both SVM techniques implemented in the WEKA-KNIME LibSVM node, the following default parameters were used: kernel cache (cache size = 40.0), kernel type is radial basis function: exp(-gamma*|u-v|2), loss function is 0.1, kernel coefficients epsilon = 0.001 and Gamma = 0.00.

Techniques: Biomarker Discovery

Accuracy, cohen’s κ, TPR, and TNR values based for the all ML tools and using either 5-fold cross validation or 20% testing set for prediction people with T2DM from people without T2DM.

Journal: PLoS ONE

Article Title: Investigating the association of CD36 gene polymorphisms (rs1761667 and rs1527483) with T2DM and dyslipidemia: Statistical analysis, machine learning based prediction, and meta-analysis

doi: 10.1371/journal.pone.0257857

Figure Lengend Snippet: Accuracy, cohen’s κ, TPR, and TNR values based for the all ML tools and using either 5-fold cross validation or 20% testing set for prediction people with T2DM from people without T2DM.

Article Snippet: In both SVM techniques implemented in the WEKA-KNIME LibSVM node, the following default parameters were used: kernel cache (cache size = 40.0), kernel type is radial basis function: exp(-gamma*|u-v|2), loss function is 0.1, kernel coefficients epsilon = 0.001 and Gamma = 0.00.

Techniques: Biomarker Discovery