<p>Macro F-measure across feature selection schemes, subsets of features and classifier.</p
<p>F1-measure of the proposed with user provided skimming ratio (F1-Geometric) and default skimming ...
Details of the multi-view data sets used in our experiments (feature type (dimensionality)).</p
<p>The performance of different classifiers associated with the attribute selection methods assessed...
<p>The values of Macro-Precision, Macro-Recall, Macro-F1 and Micro-F1 under different number of feat...
<p>Mean (and median) macro F<sub>1</sub>-scores of the segmentation methods for the IF and LIVE imag...
<p>F-measure measurement of the ESA-ELM and the SA-ELM for each language separately.</p
<p>The values of Macro-Precision, Macro-Recall, Macro-F1 and Micro-F1 under different topic features...
Measures for the entire set of items and the subscales for Mokken scale analysis.</p
<p>The values of Macro-Precision, Macro-Recall, Macro-F1 and Micro-F1 under different number of feat...
<p>The feature dimension of the sparse feature subsets and the full features.</p
<p>The winning frequency is calculated for different feature selection methods for various sizes of ...
<p>Performance evaluation of various classifier and feature selection methods.</p
<p>F1-measure results for the local context kernel with combination of different feature sets: Negat...
Features of the stimulus set: Descriptive and distributional measures for each variable.</p
<p>Black, blue and green lines respectively represent the classification score (<i>precision</i>) ob...
<p>F1-measure of the proposed with user provided skimming ratio (F1-Geometric) and default skimming ...
Details of the multi-view data sets used in our experiments (feature type (dimensionality)).</p
<p>The performance of different classifiers associated with the attribute selection methods assessed...
<p>The values of Macro-Precision, Macro-Recall, Macro-F1 and Micro-F1 under different number of feat...
<p>Mean (and median) macro F<sub>1</sub>-scores of the segmentation methods for the IF and LIVE imag...
<p>F-measure measurement of the ESA-ELM and the SA-ELM for each language separately.</p
<p>The values of Macro-Precision, Macro-Recall, Macro-F1 and Micro-F1 under different topic features...
Measures for the entire set of items and the subscales for Mokken scale analysis.</p
<p>The values of Macro-Precision, Macro-Recall, Macro-F1 and Micro-F1 under different number of feat...
<p>The feature dimension of the sparse feature subsets and the full features.</p
<p>The winning frequency is calculated for different feature selection methods for various sizes of ...
<p>Performance evaluation of various classifier and feature selection methods.</p
<p>F1-measure results for the local context kernel with combination of different feature sets: Negat...
Features of the stimulus set: Descriptive and distributional measures for each variable.</p
<p>Black, blue and green lines respectively represent the classification score (<i>precision</i>) ob...
<p>F1-measure of the proposed with user provided skimming ratio (F1-Geometric) and default skimming ...
Details of the multi-view data sets used in our experiments (feature type (dimensionality)).</p
<p>The performance of different classifiers associated with the attribute selection methods assessed...
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