svm environment 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, 2026-03
90/100 stars
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svm model  (Johns Hopkins HealthCare)
90
Johns Hopkins HealthCare svm model
a.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the originally published LDA model in women without a psychiatric history. b.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the <t>SVM</t> model in women without a psychiatric history. c.) Plot of EPDS threshold values (x axis) as a function of the mean model output (predicted probability) for women above the EPDS threshold minus that for women below the threshold (y axis) for the originally published LDA model in women without a psychiatric history. d.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the SVM model in women with a previous history <t>of</t> <t>PPD.</t> e.) Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the SVM model in women with a previous history of PPD. f.)Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the SVM model in women without a psychiatric history. g.) Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the novelly SVM model accounting for antenatal depression status in a combined sample of women with and without a previous history of PPD. h.)Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the novelly SVM model accounting for antenatal depression status in a combined sample of women with and without a previous history of PPD. Horizontal dashed red lines denote an AUC of 70% while a dashed vertical black line denotes an EPDS of ≥ 13, signifying likely PPD.
Svm Model, supplied by Johns Hopkins HealthCare, 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 model/product/Johns Hopkins HealthCare
Average 90 stars, based on 1 article reviews
svm model - by Bioz Stars, 2026-03
90/100 stars
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matlab 2015a  (MathWorks Inc)
90
MathWorks Inc matlab 2015a
a.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the originally published LDA model in women without a psychiatric history. b.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the <t>SVM</t> model in women without a psychiatric history. c.) Plot of EPDS threshold values (x axis) as a function of the mean model output (predicted probability) for women above the EPDS threshold minus that for women below the threshold (y axis) for the originally published LDA model in women without a psychiatric history. d.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the SVM model in women with a previous history <t>of</t> <t>PPD.</t> e.) Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the SVM model in women with a previous history of PPD. f.)Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the SVM model in women without a psychiatric history. g.) Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the novelly SVM model accounting for antenatal depression status in a combined sample of women with and without a previous history of PPD. h.)Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the novelly SVM model accounting for antenatal depression status in a combined sample of women with and without a previous history of PPD. Horizontal dashed red lines denote an AUC of 70% while a dashed vertical black line denotes an EPDS of ≥ 13, signifying likely PPD.
Matlab 2015a, supplied by MathWorks Inc, 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/matlab 2015a/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
matlab 2015a - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier
svm classifier implementation  (SourceForge net)
90
SourceForge net svm classifier implementation
a.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the originally published LDA model in women without a psychiatric history. b.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the <t>SVM</t> model in women without a psychiatric history. c.) Plot of EPDS threshold values (x axis) as a function of the mean model output (predicted probability) for women above the EPDS threshold minus that for women below the threshold (y axis) for the originally published LDA model in women without a psychiatric history. d.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the SVM model in women with a previous history <t>of</t> <t>PPD.</t> e.) Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the SVM model in women with a previous history of PPD. f.)Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the SVM model in women without a psychiatric history. g.) Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the novelly SVM model accounting for antenatal depression status in a combined sample of women with and without a previous history of PPD. h.)Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the novelly SVM model accounting for antenatal depression status in a combined sample of women with and without a previous history of PPD. Horizontal dashed red lines denote an AUC of 70% while a dashed vertical black line denotes an EPDS of ≥ 13, signifying likely PPD.
Svm Classifier Implementation, supplied by SourceForge net, 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 classifier implementation/product/SourceForge net
Average 90 stars, based on 1 article reviews
svm classifier implementation - by Bioz Stars, 2026-03
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

a.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the originally published LDA model in women without a psychiatric history. b.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the SVM model in women without a psychiatric history. c.) Plot of EPDS threshold values (x axis) as a function of the mean model output (predicted probability) for women above the EPDS threshold minus that for women below the threshold (y axis) for the originally published LDA model in women without a psychiatric history. d.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the SVM model in women with a previous history of PPD. e.) Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the SVM model in women with a previous history of PPD. f.)Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the SVM model in women without a psychiatric history. g.) Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the novelly SVM model accounting for antenatal depression status in a combined sample of women with and without a previous history of PPD. h.)Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the novelly SVM model accounting for antenatal depression status in a combined sample of women with and without a previous history of PPD. Horizontal dashed red lines denote an AUC of 70% while a dashed vertical black line denotes an EPDS of ≥ 13, signifying likely PPD.

Journal: Psychiatry research

Article Title: DNA methylation biomarkers prospectively predict both antenatal and postpartum depression

doi: 10.1016/j.psychres.2019.112711

Figure Lengend Snippet: a.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the originally published LDA model in women without a psychiatric history. b.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the SVM model in women without a psychiatric history. c.) Plot of EPDS threshold values (x axis) as a function of the mean model output (predicted probability) for women above the EPDS threshold minus that for women below the threshold (y axis) for the originally published LDA model in women without a psychiatric history. d.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the SVM model in women with a previous history of PPD. e.) Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the SVM model in women with a previous history of PPD. f.)Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the SVM model in women without a psychiatric history. g.) Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the novelly SVM model accounting for antenatal depression status in a combined sample of women with and without a previous history of PPD. h.)Plot of EPDS threshold values (x axis) as a function of the mean model output for women above the EPDS threshold minus that for women below the threshold (y axis) for the novelly SVM model accounting for antenatal depression status in a combined sample of women with and without a previous history of PPD. Horizontal dashed red lines denote an AUC of 70% while a dashed vertical black line denotes an EPDS of ≥ 13, signifying likely PPD.

Article Snippet: From a practical standpoint, in order to generate a model with the potential to be efficacious in a clinical environment, we trained a new SVM model on the Johns Hopkins Prospective PPD cohort data incorporating antenatal depression status as an interaction covariate in the model. We applied this to the combined UC Irvine cohort, inputting previous history of PPD as the interacting covariate and observed significant correlations of predictive accuracy with increasing depression severity (T1: Rho= 0.94, p = 0, T2: Rho= 0.91, p = 0, T3: Rho= 0.57, p = 0.013) with T3 samples achieving an AUC of 0.77 (95% CI: 0.64–0.77) to detect an EPDS ≥ 13 ( ).

Techniques:

a.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the SVM model accounting for antenatal depression status in women from the UC Irvine cohort where antenatal depression status is determined with T1 time point biomarker output. b.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the SVM model accounting for antenatal depression status in the JHU Prospective Neuroimaging cohort. Horizontal dashed red lines denote an AUC of 70% while a dashed vertical black line denotes an EPDS of ≥ 13, signifying likely PPD. c.) A plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for an SVM model to detect PPD status trained on a model incorporating variation in both TTC9B and HP1BP3 across three technical replicates in a subset of N = 20 women from the JHU Prospective Neuroimaging cohort. Horizontal dashed red lines denote an AUC of 80%.

Journal: Psychiatry research

Article Title: DNA methylation biomarkers prospectively predict both antenatal and postpartum depression

doi: 10.1016/j.psychres.2019.112711

Figure Lengend Snippet: a.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the SVM model accounting for antenatal depression status in women from the UC Irvine cohort where antenatal depression status is determined with T1 time point biomarker output. b.)Plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for the SVM model accounting for antenatal depression status in the JHU Prospective Neuroimaging cohort. Horizontal dashed red lines denote an AUC of 70% while a dashed vertical black line denotes an EPDS of ≥ 13, signifying likely PPD. c.) A plot of EPDS threshold values (x axis) as a function of the AUC of prediction for the number of women above that threshold (y axis) for an SVM model to detect PPD status trained on a model incorporating variation in both TTC9B and HP1BP3 across three technical replicates in a subset of N = 20 women from the JHU Prospective Neuroimaging cohort. Horizontal dashed red lines denote an AUC of 80%.

Article Snippet: From a practical standpoint, in order to generate a model with the potential to be efficacious in a clinical environment, we trained a new SVM model on the Johns Hopkins Prospective PPD cohort data incorporating antenatal depression status as an interaction covariate in the model. We applied this to the combined UC Irvine cohort, inputting previous history of PPD as the interacting covariate and observed significant correlations of predictive accuracy with increasing depression severity (T1: Rho= 0.94, p = 0, T2: Rho= 0.91, p = 0, T3: Rho= 0.57, p = 0.013) with T3 samples achieving an AUC of 0.77 (95% CI: 0.64–0.77) to detect an EPDS ≥ 13 ( ).

Techniques: Biomarker Discovery