<p>Barcharts: (a) comparison of dataset-wise average accuracies, and (b) comparison of dataset-wise average MCCs, among our proposed and other existing rule-based classifiers for the four datasets.</p
Predictive accuracies of classifiers against benchmark datasets with varying percentages of retained...
<p>Comparison of average classification results of different classifiers without using light intensi...
Motivation: There is growing discussion in the bioinformatics community concerning overoptimism of r...
<p>Comparison of the average classification accuracies of different algorithms for different numbers...
<p>Comparative performance analysis of the rule-based classifiers on Dataset 4, respectively (at 4-f...
<p>Comparative performance analysis of the rule-based classifiers on Dataset 1, respectively (at 4-f...
<p>Classification accuracies of distinct classification methods for Baranzini dataset and Goertsches...
<p>Comparative performance analysis of the rule-based classifiers on Dataset 2, respectively (at 4-f...
Comparison of classification accuracies of dataset 1 with different classifiers.</p
The points represent the mean MCCs as each of the 25 datasets was iteratively used as training set t...
Comparison of classification accuracies of dataset 2 with different classifiers.</p
This research uses four classification algorithms in standard and boosted forms to predict members o...
<p>Classification accuracies of different discretization methods for Baranzini dataset and Goertsche...
<p>A series of classifiers can be constructed using different number of top features from the mRMR t...
<p>Comparison of classification results obtained through 5-fold cross validation with respect to dif...
Predictive accuracies of classifiers against benchmark datasets with varying percentages of retained...
<p>Comparison of average classification results of different classifiers without using light intensi...
Motivation: There is growing discussion in the bioinformatics community concerning overoptimism of r...
<p>Comparison of the average classification accuracies of different algorithms for different numbers...
<p>Comparative performance analysis of the rule-based classifiers on Dataset 4, respectively (at 4-f...
<p>Comparative performance analysis of the rule-based classifiers on Dataset 1, respectively (at 4-f...
<p>Classification accuracies of distinct classification methods for Baranzini dataset and Goertsches...
<p>Comparative performance analysis of the rule-based classifiers on Dataset 2, respectively (at 4-f...
Comparison of classification accuracies of dataset 1 with different classifiers.</p
The points represent the mean MCCs as each of the 25 datasets was iteratively used as training set t...
Comparison of classification accuracies of dataset 2 with different classifiers.</p
This research uses four classification algorithms in standard and boosted forms to predict members o...
<p>Classification accuracies of different discretization methods for Baranzini dataset and Goertsche...
<p>A series of classifiers can be constructed using different number of top features from the mRMR t...
<p>Comparison of classification results obtained through 5-fold cross validation with respect to dif...
Predictive accuracies of classifiers against benchmark datasets with varying percentages of retained...
<p>Comparison of average classification results of different classifiers without using light intensi...
Motivation: There is growing discussion in the bioinformatics community concerning overoptimism of r...