<p>SVM based performance on testing dataset (5-fold cross-validation) using parameters t = 2 (RBF kernel), and g = 1, c = 0.1, j = 2.</p
<p>The 10-fold cross-validation results of independent test by SVM algorithm with g = 0.005 and cuto...
Tuning the regularisation and kernel hyperparameters is a vital step in optimising the generalisatio...
<p>Comparison of kernelPLS with four other methods. For 5-fold cross validation classification accur...
<p>Performance of SVM model for various combinations of genes tested. RBF kernel function (γ value =...
<p>The generalized performance of the SVM model. We rebuilt the model for 100 times for the validati...
<p>The Performance of SVM Models on validation dataset with experimentally derived binding affinity ...
<p>The accuracy from 5-fold cross validation of SVM using EVSA and GDDA as kernel.</p
<p>Comparison of kernelPLS with four other methods. For 10-fold cross validation classification accu...
Features are removed cumulatively, that is each row represents performance when removing all feature...
<p>Optimization of the parameters <i>C</i> and γ of the SVM kernel RBF: only <i>C</i> values of 0.01...
<p>Using binary patterns and AA (amino acid) composition [γ <b>(g)</b> (in RBF kernel), c: parameter...
Artificial intelligence (AI) and machine learning (ML) have influenced every part of our day-to-day ...
<p>The best cross-validation results of linear kernel and RBF kernel after grid searches on WP datas...
<p>SVM model is tested by three different datasets, only genotype, only phenotype and integrated phe...
<p>The Performance of SVM Models on PSSM based training dataset D3 & D4 with different learning para...
<p>The 10-fold cross-validation results of independent test by SVM algorithm with g = 0.005 and cuto...
Tuning the regularisation and kernel hyperparameters is a vital step in optimising the generalisatio...
<p>Comparison of kernelPLS with four other methods. For 5-fold cross validation classification accur...
<p>Performance of SVM model for various combinations of genes tested. RBF kernel function (γ value =...
<p>The generalized performance of the SVM model. We rebuilt the model for 100 times for the validati...
<p>The Performance of SVM Models on validation dataset with experimentally derived binding affinity ...
<p>The accuracy from 5-fold cross validation of SVM using EVSA and GDDA as kernel.</p
<p>Comparison of kernelPLS with four other methods. For 10-fold cross validation classification accu...
Features are removed cumulatively, that is each row represents performance when removing all feature...
<p>Optimization of the parameters <i>C</i> and γ of the SVM kernel RBF: only <i>C</i> values of 0.01...
<p>Using binary patterns and AA (amino acid) composition [γ <b>(g)</b> (in RBF kernel), c: parameter...
Artificial intelligence (AI) and machine learning (ML) have influenced every part of our day-to-day ...
<p>The best cross-validation results of linear kernel and RBF kernel after grid searches on WP datas...
<p>SVM model is tested by three different datasets, only genotype, only phenotype and integrated phe...
<p>The Performance of SVM Models on PSSM based training dataset D3 & D4 with different learning para...
<p>The 10-fold cross-validation results of independent test by SVM algorithm with g = 0.005 and cuto...
Tuning the regularisation and kernel hyperparameters is a vital step in optimising the generalisatio...
<p>Comparison of kernelPLS with four other methods. For 5-fold cross validation classification accur...
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