<p>Box plots illustrating differences in performance (AUC and MCC) of 10 optimized SVM component models built for all training classes generated for MACCS FP and a training ratio of 0.40.</p
<p>Segmentation performance of different models in terms of Se, Sp, Acc and Auc.</p
(a) exhibits performance of different deep learning architectures in comparison with SMFM, each box ...
<p>The Performance of SVM Models on validation dataset with experimentally derived binding affinity ...
<p>(a) ACC, (b) BACC, (c) MCC, and (d) AUC of five SVM models trained on 5 different data sets (trai...
<p>Performance of four SVM modules (AAC, DPC, SAAC, Hybrid) by the receiver operating characteristic...
The plot shows the predictive performances for the different methods when normalized data were class...
<p>The Performance of SVM Models on PSSM based training dataset D3 & D4 with different learning para...
<p>Average AUC and accuracy of the (a) SVM and (b) PLS models containing different numbers of featur...
<p>Measured by the area under the ROC curve (AUC), classification performance is shown for models co...
<p>SVM model is tested by three different datasets, only genotype, only phenotype and integrated phe...
<p>A. The histogram shows the score distribution of the instances in the positive bags and the negat...
<p>Performance was evaluated based on the AUC scores using independent tests.</p
<p>Upper panel, frequency distributions of classification patterns identified by the SVM composite m...
<p>Using binary patterns and AA (amino acid) composition [γ <b>(g)</b> (in RBF kernel), c: parameter...
<p>Top left panel shows boxplots of the area under the curve (AUC) for test data. The top right pane...
<p>Segmentation performance of different models in terms of Se, Sp, Acc and Auc.</p
(a) exhibits performance of different deep learning architectures in comparison with SMFM, each box ...
<p>The Performance of SVM Models on validation dataset with experimentally derived binding affinity ...
<p>(a) ACC, (b) BACC, (c) MCC, and (d) AUC of five SVM models trained on 5 different data sets (trai...
<p>Performance of four SVM modules (AAC, DPC, SAAC, Hybrid) by the receiver operating characteristic...
The plot shows the predictive performances for the different methods when normalized data were class...
<p>The Performance of SVM Models on PSSM based training dataset D3 & D4 with different learning para...
<p>Average AUC and accuracy of the (a) SVM and (b) PLS models containing different numbers of featur...
<p>Measured by the area under the ROC curve (AUC), classification performance is shown for models co...
<p>SVM model is tested by three different datasets, only genotype, only phenotype and integrated phe...
<p>A. The histogram shows the score distribution of the instances in the positive bags and the negat...
<p>Performance was evaluated based on the AUC scores using independent tests.</p
<p>Upper panel, frequency distributions of classification patterns identified by the SVM composite m...
<p>Using binary patterns and AA (amino acid) composition [γ <b>(g)</b> (in RBF kernel), c: parameter...
<p>Top left panel shows boxplots of the area under the curve (AUC) for test data. The top right pane...
<p>Segmentation performance of different models in terms of Se, Sp, Acc and Auc.</p
(a) exhibits performance of different deep learning architectures in comparison with SMFM, each box ...
<p>The Performance of SVM Models on validation dataset with experimentally derived binding affinity ...