*<p>ReliefF and MRMR are ranking procedures. The optimal sets of features for these two methods were determined for each classifier separately; the number of features (shown in parentheses) corresponds to the size of the subset of features characterized by the smallest cross validation error for the specific classifier.</p
<p>The 5-fold CV classification accuracies of the KNN-classifier and SVM-classifier based on six gen...
In the machine learning field the performance of a classifier is usually measured in terms of predic...
<p>The upper panel illustrates the combination of the inner cross-validation loop, which is used to ...
*<p>ReliefF and MRMR are ranking procedures. The optimal sets of features for these two methods were...
<p>The apparent error rate (<i>AE</i>) and the cross-validation error (<i>CVE</i>) in different feat...
<p>Comparison of classification results obtained through 5-fold cross validation with respect to dif...
Given the relatively small number of microarrays typically used in gene-expression-based classificat...
Various discriminant methods have been applied for classification of tumors based on gene expression...
<p>The apparent error rate (<i>AE</i>) and the cross-validation error (<i>CVE</i>) in different feat...
Abstract Background Cross-validation (CV) is an effective method for estimating the prediction error...
<p>The 5-fold CV classification accuracies of the KNN-classifier and SVM-classifier based on six gen...
Motivation. Binary classification is a common problem in many types of research including clinical a...
<p>The 5-fold CV classification accuracies of the KNN-classifier and SVM-classifier based on six gen...
<p>Evaluation of multiple classification models including Support Vector Machine (SVM), Random Fores...
<p><b>Copyright information:</b></p><p>Taken from "Impact of image segmentation on high-content scre...
<p>The 5-fold CV classification accuracies of the KNN-classifier and SVM-classifier based on six gen...
In the machine learning field the performance of a classifier is usually measured in terms of predic...
<p>The upper panel illustrates the combination of the inner cross-validation loop, which is used to ...
*<p>ReliefF and MRMR are ranking procedures. The optimal sets of features for these two methods were...
<p>The apparent error rate (<i>AE</i>) and the cross-validation error (<i>CVE</i>) in different feat...
<p>Comparison of classification results obtained through 5-fold cross validation with respect to dif...
Given the relatively small number of microarrays typically used in gene-expression-based classificat...
Various discriminant methods have been applied for classification of tumors based on gene expression...
<p>The apparent error rate (<i>AE</i>) and the cross-validation error (<i>CVE</i>) in different feat...
Abstract Background Cross-validation (CV) is an effective method for estimating the prediction error...
<p>The 5-fold CV classification accuracies of the KNN-classifier and SVM-classifier based on six gen...
Motivation. Binary classification is a common problem in many types of research including clinical a...
<p>The 5-fold CV classification accuracies of the KNN-classifier and SVM-classifier based on six gen...
<p>Evaluation of multiple classification models including Support Vector Machine (SVM), Random Fores...
<p><b>Copyright information:</b></p><p>Taken from "Impact of image segmentation on high-content scre...
<p>The 5-fold CV classification accuracies of the KNN-classifier and SVM-classifier based on six gen...
In the machine learning field the performance of a classifier is usually measured in terms of predic...
<p>The upper panel illustrates the combination of the inner cross-validation loop, which is used to ...