<p><i>Note:</i> **Accuracy with feature selection is significant higher than that without feature selection, <i>p</i><.01.</p
<p>The classification accuracy for various feature subsets, averaged over all the class definitions....
<p>Mean classification accuracy of 25 independent simulations plotted as a function of number of tra...
<p>(A) Classification accuracy when the number of channels was reduced. The bold black, red, and blu...
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
The main purpose of Feature Subset Selection is to find a reduced subset of attributes from a data ...
<p>Classification accuracy (%) for all subjects using different feature extraction methods.</p
<p>Accuracy is shown for classifiers based on recursive feature elimination (solid blue line), rando...
<p><i>Note:</i> NS: No couples of electrodes were selected since there was no main effect among emot...
Abstract. Feature selection is a process followed in order to improve the generalization and the per...
In machine learning the classification task is normally known as supervised learning. In supervised ...
Train and test accuracy for selected classifiers for different projection methods.</p
<p><i>Note:</i> **Accuracy with feature selection is significant higher than that without feature se...
<p><i>Note:</i> NS: No couples of electrodes were selected since there was no main effect among emot...
<p>The performance is represented in terms of accuracy, sensitivity and specificity in classifying S...
AbstractFeature selection has become interest to many research areas which deal with machine learnin...
<p>The classification accuracy for various feature subsets, averaged over all the class definitions....
<p>Mean classification accuracy of 25 independent simulations plotted as a function of number of tra...
<p>(A) Classification accuracy when the number of channels was reduced. The bold black, red, and blu...
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
The main purpose of Feature Subset Selection is to find a reduced subset of attributes from a data ...
<p>Classification accuracy (%) for all subjects using different feature extraction methods.</p
<p>Accuracy is shown for classifiers based on recursive feature elimination (solid blue line), rando...
<p><i>Note:</i> NS: No couples of electrodes were selected since there was no main effect among emot...
Abstract. Feature selection is a process followed in order to improve the generalization and the per...
In machine learning the classification task is normally known as supervised learning. In supervised ...
Train and test accuracy for selected classifiers for different projection methods.</p
<p><i>Note:</i> **Accuracy with feature selection is significant higher than that without feature se...
<p><i>Note:</i> NS: No couples of electrodes were selected since there was no main effect among emot...
<p>The performance is represented in terms of accuracy, sensitivity and specificity in classifying S...
AbstractFeature selection has become interest to many research areas which deal with machine learnin...
<p>The classification accuracy for various feature subsets, averaged over all the class definitions....
<p>Mean classification accuracy of 25 independent simulations plotted as a function of number of tra...
<p>(A) Classification accuracy when the number of channels was reduced. The bold black, red, and blu...
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