Clustering data has been of great interest to many researchers. Hierarchical clustering methods have been preferred because clusters can be visualized as a dendrogram. One of the problems of hierarchical clustering methods, however, is that the resulting dendrogram is not visually pleasing due to the scaling problem. Hence, a series of iterated logarithmic function is proposed so as to mitigate the scaling problem. Theoretical properties of the iterated logarithmic function are presented. I
<p>Clustering results from the selected cut levels. Bilaterally symmetric clusters are displayed in ...
International audienceWe present a novel hierarchical graph clustering algorithm inspired by modular...
<p>Based on the log10(IC20), the clustering used the Euclidean dissimilarity measure. A. Heat map re...
In hierarchical cluster analysis, dendrograms are used to visualize how clusters are formed. I propo...
Abstract. In hierarchical cluster analysis, dendrograms are used to visualize how clusters are forme...
Hierarchical clustering algorithms are typically more effective in detecting the true clustering str...
International audienceThe classical representation of a binary tree generated by a hierarchical clus...
Abstract-The classical representation of a binary tree generated by a hierarchical clustering is a n...
The vertical axis of the dendrogram represents the distance or dissimilarity between labeled cluster...
BackgroundHierarchical cluster analysis (HCA) is a widely used classificatory technique in many area...
Both the x-axis and the y-axis are on the logarithmic scale. The main takeaway is that nodes with sm...
International audienceHierarchical clustering can traditionally be represented through a dendrogram:...
International audienceAgglomerative clustering methods have been widely used by many research commun...
Dendrogram resulting from hierachical clustering analysis and presenting different clusters of corre...
Hierarchical Clustering. Hierarchical clustering methods construct a dendro-gram of the input datase...
<p>Clustering results from the selected cut levels. Bilaterally symmetric clusters are displayed in ...
International audienceWe present a novel hierarchical graph clustering algorithm inspired by modular...
<p>Based on the log10(IC20), the clustering used the Euclidean dissimilarity measure. A. Heat map re...
In hierarchical cluster analysis, dendrograms are used to visualize how clusters are formed. I propo...
Abstract. In hierarchical cluster analysis, dendrograms are used to visualize how clusters are forme...
Hierarchical clustering algorithms are typically more effective in detecting the true clustering str...
International audienceThe classical representation of a binary tree generated by a hierarchical clus...
Abstract-The classical representation of a binary tree generated by a hierarchical clustering is a n...
The vertical axis of the dendrogram represents the distance or dissimilarity between labeled cluster...
BackgroundHierarchical cluster analysis (HCA) is a widely used classificatory technique in many area...
Both the x-axis and the y-axis are on the logarithmic scale. The main takeaway is that nodes with sm...
International audienceHierarchical clustering can traditionally be represented through a dendrogram:...
International audienceAgglomerative clustering methods have been widely used by many research commun...
Dendrogram resulting from hierachical clustering analysis and presenting different clusters of corre...
Hierarchical Clustering. Hierarchical clustering methods construct a dendro-gram of the input datase...
<p>Clustering results from the selected cut levels. Bilaterally symmetric clusters are displayed in ...
International audienceWe present a novel hierarchical graph clustering algorithm inspired by modular...
<p>Based on the log10(IC20), the clustering used the Euclidean dissimilarity measure. A. Heat map re...