<p>The results have been run 20 times for every feature construction by SVM algorithm with g = 0.005 and cutoff = 0.5. The values are mean ± standard variance. The results of MDD-SOH were obtained in 5-fold cross-validation.</p
<p>The balanced accuracies were calculated by 10-fold cross-validation. Values represent the mean ± ...
<p>Results for feature selection, model selection and validation, using the two selection criteria a...
<p>The prediction results compared with other methods on the training dataset using 10-fold cross-va...
<p>The 10-fold cross-validation results of independent test by SVM algorithm with g = 0.005 and cuto...
<p>Total 1783 cysteine sequences were applied in positive and negative data. Sn, sensitivity; Sp, sp...
Five-fold cross-validation results performed by SVM classifier combined with the proposed feature de...
<p>(a) Values for TPR, TNR, PPV, and NPV. (b) Values for MCC, BACC, AUC, and ACC.</p
<p>The data set is partitioned into 10 parts (folds) in the outer loop. One fold of the data set is ...
<p>10% of the data were defined as test dataset (TestData1) while the remaining 90% (TrainingData1) ...
<p>The generalized performance of the SVM model. We rebuilt the model for 100 times for the validati...
A. Balanced Accuracies for the population-level classifier using the generic STM representation as i...
<p>10-fold cross-validation of static SSVEP classification by the quantity of training data.</p
<p>The mean squared error (MSE) for the model with highest is given for both the training set (90% ...
*<p>The latter number represents standard deviation from 10 training set;</p>**<p>the lower right co...
(A) We used recordings from the SHHS dataset [34, 35]. For each subject, we low-pass filtered, downs...
<p>The balanced accuracies were calculated by 10-fold cross-validation. Values represent the mean ± ...
<p>Results for feature selection, model selection and validation, using the two selection criteria a...
<p>The prediction results compared with other methods on the training dataset using 10-fold cross-va...
<p>The 10-fold cross-validation results of independent test by SVM algorithm with g = 0.005 and cuto...
<p>Total 1783 cysteine sequences were applied in positive and negative data. Sn, sensitivity; Sp, sp...
Five-fold cross-validation results performed by SVM classifier combined with the proposed feature de...
<p>(a) Values for TPR, TNR, PPV, and NPV. (b) Values for MCC, BACC, AUC, and ACC.</p
<p>The data set is partitioned into 10 parts (folds) in the outer loop. One fold of the data set is ...
<p>10% of the data were defined as test dataset (TestData1) while the remaining 90% (TrainingData1) ...
<p>The generalized performance of the SVM model. We rebuilt the model for 100 times for the validati...
A. Balanced Accuracies for the population-level classifier using the generic STM representation as i...
<p>10-fold cross-validation of static SSVEP classification by the quantity of training data.</p
<p>The mean squared error (MSE) for the model with highest is given for both the training set (90% ...
*<p>The latter number represents standard deviation from 10 training set;</p>**<p>the lower right co...
(A) We used recordings from the SHHS dataset [34, 35]. For each subject, we low-pass filtered, downs...
<p>The balanced accuracies were calculated by 10-fold cross-validation. Values represent the mean ± ...
<p>Results for feature selection, model selection and validation, using the two selection criteria a...
<p>The prediction results compared with other methods on the training dataset using 10-fold cross-va...
DOI
Add to ORKG