This paper shows a new combinatorial problem which emerged from studies on an artificial intelligence classification model of a hierarchical classifier. We introduce the notion of proper clustering and show how to count their number in a special case when 3 clusters are allowed. An algorithm that generates all clusterings is given. We also show that the proposed approach can be generalized to any number of clusters, and can be automatized. Finally, we show the relationship between the problem of counting clusterings and the Dedekind problem
Hierarchical clustering is a recursive partitioning of a dataset into clusters at an increasingly fi...
The issue of determining ‘the right number of clusters’ is attracting ever growing interest. The pap...
Abstract:- In this paper a new clustering criterion for the struc uralization of universes in the Lo...
This paper shows a new combinatorial problem which emerged from studies on an artificial intelligenc...
This paper shows a new combinatorial problem which emerged from studies on an arti cial intelligenc...
Abstract: A fundamental and difficult problem in cluster analysis is the determination of the “true...
Clustering is one of the most popular artificial intelligence techniques which aims at identifying g...
Determining an optimal number of clusters and producing reliable results are two challenging and cri...
In this paper we present an unsupervised algorithm which performs clustering given a data set and wh...
Determining the number of clusters is one of the most important topics in cluster analysis. The abil...
We survey agglomerative hierarchical clustering algorithms and discuss efficient implementations tha...
Hierarchical clustering is typically implemented as a greedy heuristic algorithm with no explicit ob...
We propose a clustering method which produces valid results while automatically determining an optim...
Hierarchical clustering is typically implemented as a greedy heuristic algorithm with no explicit ob...
This paper explores hierarchical clustering in the case where pairs of points have dissimilarity sco...
Hierarchical clustering is a recursive partitioning of a dataset into clusters at an increasingly fi...
The issue of determining ‘the right number of clusters’ is attracting ever growing interest. The pap...
Abstract:- In this paper a new clustering criterion for the struc uralization of universes in the Lo...
This paper shows a new combinatorial problem which emerged from studies on an artificial intelligenc...
This paper shows a new combinatorial problem which emerged from studies on an arti cial intelligenc...
Abstract: A fundamental and difficult problem in cluster analysis is the determination of the “true...
Clustering is one of the most popular artificial intelligence techniques which aims at identifying g...
Determining an optimal number of clusters and producing reliable results are two challenging and cri...
In this paper we present an unsupervised algorithm which performs clustering given a data set and wh...
Determining the number of clusters is one of the most important topics in cluster analysis. The abil...
We survey agglomerative hierarchical clustering algorithms and discuss efficient implementations tha...
Hierarchical clustering is typically implemented as a greedy heuristic algorithm with no explicit ob...
We propose a clustering method which produces valid results while automatically determining an optim...
Hierarchical clustering is typically implemented as a greedy heuristic algorithm with no explicit ob...
This paper explores hierarchical clustering in the case where pairs of points have dissimilarity sco...
Hierarchical clustering is a recursive partitioning of a dataset into clusters at an increasingly fi...
The issue of determining ‘the right number of clusters’ is attracting ever growing interest. The pap...
Abstract:- In this paper a new clustering criterion for the struc uralization of universes in the Lo...