<p>NC classifier trained as a function of the number of samples in a -fold CV setting for each of the four datasets. We show here the accuracy for 100-gene signatures.</p
<p>The bar plots correspond to the average area under the ROC curve obtained from five widely used s...
<p>The colors of the lines correspond to the six reference genome sets (ALL, BAAC, BAS, BAC, GAMMA a...
<p>(A) ROC curve for the HIV-RT classifier. (B) ROC curve for the adenosine receptors classifier. (C...
<p>NC classifier trained as a function of the number of samples in a -fold CV setting. We show here ...
<p>NC classifier trained as a function of the size of the signature, for different feature selection...
<p>Classification performance was measured as area under the curve (AUC) of the ROC curve. A perfect...
<p>The receiver operator characteristic (ROC) curve of a simple threshold classifier over all datase...
(A) ROC curves for simulated whole-exome sequencing data, for one cancer type versus all others. Are...
<p>In this case, the Area Under the ROC Curve (AUC) of the non-bootstrapped SPACE method was 0.748, ...
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) c...
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) c...
<p>ROC curves and area under ROC curve (AUC) values can be used as more robust measures of classifie...
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) c...
Receiver operating characteristic (ROC) curves are widely used for evaluating classifier performance...
<p>*ROC plot for diagnostic accuracy presents true positive rate vs. false positive rate (or sensiti...
<p>The bar plots correspond to the average area under the ROC curve obtained from five widely used s...
<p>The colors of the lines correspond to the six reference genome sets (ALL, BAAC, BAS, BAC, GAMMA a...
<p>(A) ROC curve for the HIV-RT classifier. (B) ROC curve for the adenosine receptors classifier. (C...
<p>NC classifier trained as a function of the number of samples in a -fold CV setting. We show here ...
<p>NC classifier trained as a function of the size of the signature, for different feature selection...
<p>Classification performance was measured as area under the curve (AUC) of the ROC curve. A perfect...
<p>The receiver operator characteristic (ROC) curve of a simple threshold classifier over all datase...
(A) ROC curves for simulated whole-exome sequencing data, for one cancer type versus all others. Are...
<p>In this case, the Area Under the ROC Curve (AUC) of the non-bootstrapped SPACE method was 0.748, ...
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) c...
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) c...
<p>ROC curves and area under ROC curve (AUC) values can be used as more robust measures of classifie...
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) c...
Receiver operating characteristic (ROC) curves are widely used for evaluating classifier performance...
<p>*ROC plot for diagnostic accuracy presents true positive rate vs. false positive rate (or sensiti...
<p>The bar plots correspond to the average area under the ROC curve obtained from five widely used s...
<p>The colors of the lines correspond to the six reference genome sets (ALL, BAAC, BAS, BAC, GAMMA a...
<p>(A) ROC curve for the HIV-RT classifier. (B) ROC curve for the adenosine receptors classifier. (C...
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