<p>In detail, (A) shows the IFS-curve for the dataset <i>S</i><sub>1</sub>; (B) shows the IFS-curve for the dataset <i>S</i><sub>2</sub>; (C) shows the IFS-curve for the dataset <i>S</i><sub>3</sub>; (D) shows the IFS-curve for the dataset S<sub>4</sub>; (E) shows the IFS-curve for the dataset <i>S</i><sub>5</sub>; (F) shows the IFS-curve for the dataset <i>S</i><sub>6</sub>. The Y-axis represents the Matthews’s correlation coefficient (MCC) and the X-axis represents the number of features participating in the classification model.</p
(A) The cophenetic correlation coefficient (CCC) is calculated for 100 runs with k = 2,..,6. The CCC...
<p>(a). St. Maxime:Initial curve of TCV; (b). St. Maxime:Initial curve of Proposed Algorithm; (c). T...
Supplemental Dataset 6: Graphs of fitted values for each trait, their distributions, and significanc...
<p>The IFS curve using the MCC as its Y-axis and the number of features participating in classificat...
<p>In the IFS curve, the x-axis is the number of features used for classification, and the y-axis is...
<p>A series of classifiers can be constructed using different number of top features from the mRMR t...
<p>It shows the relationship between the prediction accuracies of the NNA predictor and the number o...
<p>By adding features one by one from higher to lower rank, 315 different feature subsets are obtain...
<p>When the first 220 features in the ranked feature list were used, <i>MCC</i> reached the maximum ...
<p>In the IFS curve, the X-axis is the number of genes used for classification, and the Y-axis is th...
<p>We used an IFS curve to determine the number of features finally used in mRMR selection. Predicti...
CorrelationDecoder estimates across models (i.e., Term, LDA, and GC-LDA), databases (i.e., Neurosynt...
<p>Graphs of correlations between six different variables and the accuracy of the guesses.</p
S6 Table. a. p-values for correlation analysis (Spearman). C57BL/6J model: P120. b. Correlation coef...
<p>The Matthews correlation coefficient (MCC) is calculated according to <a href="http://www.ploscom...
(A) The cophenetic correlation coefficient (CCC) is calculated for 100 runs with k = 2,..,6. The CCC...
<p>(a). St. Maxime:Initial curve of TCV; (b). St. Maxime:Initial curve of Proposed Algorithm; (c). T...
Supplemental Dataset 6: Graphs of fitted values for each trait, their distributions, and significanc...
<p>The IFS curve using the MCC as its Y-axis and the number of features participating in classificat...
<p>In the IFS curve, the x-axis is the number of features used for classification, and the y-axis is...
<p>A series of classifiers can be constructed using different number of top features from the mRMR t...
<p>It shows the relationship between the prediction accuracies of the NNA predictor and the number o...
<p>By adding features one by one from higher to lower rank, 315 different feature subsets are obtain...
<p>When the first 220 features in the ranked feature list were used, <i>MCC</i> reached the maximum ...
<p>In the IFS curve, the X-axis is the number of genes used for classification, and the Y-axis is th...
<p>We used an IFS curve to determine the number of features finally used in mRMR selection. Predicti...
CorrelationDecoder estimates across models (i.e., Term, LDA, and GC-LDA), databases (i.e., Neurosynt...
<p>Graphs of correlations between six different variables and the accuracy of the guesses.</p
S6 Table. a. p-values for correlation analysis (Spearman). C57BL/6J model: P120. b. Correlation coef...
<p>The Matthews correlation coefficient (MCC) is calculated according to <a href="http://www.ploscom...
(A) The cophenetic correlation coefficient (CCC) is calculated for 100 runs with k = 2,..,6. The CCC...
<p>(a). St. Maxime:Initial curve of TCV; (b). St. Maxime:Initial curve of Proposed Algorithm; (c). T...
Supplemental Dataset 6: Graphs of fitted values for each trait, their distributions, and significanc...