<p>Both algorithms were independently executed 50 times in succession. The robustness is 0.131 for the <i>K</i>-means method and 10.901 for FCM. Hence, <i>K</i>-means clustering shows better reproducibility than FCM for AIF detection.</p
Clustering is a technique that groups observations in a dataset based on the distance to the centre ...
Clustering analysis has been considered as a useful means for identifying patterns in dataset. The a...
AbstractFuzzy clustering is useful clustering technique which partitions the data set in fuzzy parti...
<p>Each algorithm was executed independently 100 times in succession, and the robustness values were...
<p>Relative to FCM, the <i>K</i>-means-based AIF shows similar TTP, higher PV, larger AUC, and narro...
<p>Comparison of the AIFs obtained using <i>k</i>-means, FCM, and AH clustering methods.</p
<p>The first sub-figure showed the optimal slice image of the randomly selected subject for clusteri...
<p>Statistical analysis of the results derived from FCM and <i>K</i>-means methods for AIF detection...
<p>Comparison of AIFs obtained using different clustering algorithms and the true AIF.</p
<p>Top: time–concentration curves for different clusters. Bottom: mean curve for <i>M</i> values of ...
<p>Comparison of AIFs obtained using different clustering methods and the true AIF.</p
<p>Top: time–concentration curves for different clusters. Bottom: mean curve for <i>M</i> values of ...
<p>Top: time–concentration curves for different clusters. Bottom: mean curve for <i>M</i> values of ...
F1 Measure of clustering accuracy for diverse methods, applied onto CyTOF datasets from [5].</p
Clustering algorithms are often used for image segmentation, aiming to group pixels by their similar...
Clustering is a technique that groups observations in a dataset based on the distance to the centre ...
Clustering analysis has been considered as a useful means for identifying patterns in dataset. The a...
AbstractFuzzy clustering is useful clustering technique which partitions the data set in fuzzy parti...
<p>Each algorithm was executed independently 100 times in succession, and the robustness values were...
<p>Relative to FCM, the <i>K</i>-means-based AIF shows similar TTP, higher PV, larger AUC, and narro...
<p>Comparison of the AIFs obtained using <i>k</i>-means, FCM, and AH clustering methods.</p
<p>The first sub-figure showed the optimal slice image of the randomly selected subject for clusteri...
<p>Statistical analysis of the results derived from FCM and <i>K</i>-means methods for AIF detection...
<p>Comparison of AIFs obtained using different clustering algorithms and the true AIF.</p
<p>Top: time–concentration curves for different clusters. Bottom: mean curve for <i>M</i> values of ...
<p>Comparison of AIFs obtained using different clustering methods and the true AIF.</p
<p>Top: time–concentration curves for different clusters. Bottom: mean curve for <i>M</i> values of ...
<p>Top: time–concentration curves for different clusters. Bottom: mean curve for <i>M</i> values of ...
F1 Measure of clustering accuracy for diverse methods, applied onto CyTOF datasets from [5].</p
Clustering algorithms are often used for image segmentation, aiming to group pixels by their similar...
Clustering is a technique that groups observations in a dataset based on the distance to the centre ...
Clustering analysis has been considered as a useful means for identifying patterns in dataset. The a...
AbstractFuzzy clustering is useful clustering technique which partitions the data set in fuzzy parti...
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