Add to ORKGAbstract:- In this paper a new clustering criterion for the struc uralization of universes in the Logical Combinatorial approach of the Pattern Recognition is introduced. The proposed criterion is based in a similarity function between objects, and obtains a partition of a data set. Besides, some examples of applications of the proposed criterion in data sets are shown
Clustering seeks to group or to lump together objects or variables that share some observed qualitie...
This paper examines the problem of clustering a sequence of objects that cannot be described with a ...
International audienceOur main goal is to introduce three clustering functions based on the central ...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
Abstract — Clustering is a technique of data mining. It aims at finding natural partitioning of data...
This paper introduces a method of data clustering that is based on linguistically specified rules, s...
During the past decade and a half, there has been a considerable growth of interest in problems of p...
The Logical Analysis of Data (LAD) is a combinatorics, optimization and logic based methodology for ...
Clustering is the unsupervised classification of patterns (observations, data items, or feature vect...
[[abstract]]An efficient clustering algorithm is proposed in an unsupervised manner to cluster the g...
Clustering is the unsupervised classification of patterns (observations, data items, or feature vect...
ia that provide significant distinctions between clustering methods and can help selecting appropria...
Clustering analysis is a crucial part of pattern recognition, which refers to the procedure of patte...
This chapter deals with basic tools useful in clustering and classification and present some commonl...
In this paper a crossed clustering algorithm is proposed to partitioning a set of symbolic objects i...
Clustering seeks to group or to lump together objects or variables that share some observed qualitie...
This paper examines the problem of clustering a sequence of objects that cannot be described with a ...
International audienceOur main goal is to introduce three clustering functions based on the central ...
Target of cluster analysis is to group data represented as a vector of measurements or a point in a ...
Abstract — Clustering is a technique of data mining. It aims at finding natural partitioning of data...
This paper introduces a method of data clustering that is based on linguistically specified rules, s...
During the past decade and a half, there has been a considerable growth of interest in problems of p...
The Logical Analysis of Data (LAD) is a combinatorics, optimization and logic based methodology for ...
Clustering is the unsupervised classification of patterns (observations, data items, or feature vect...
[[abstract]]An efficient clustering algorithm is proposed in an unsupervised manner to cluster the g...
Clustering is the unsupervised classification of patterns (observations, data items, or feature vect...
ia that provide significant distinctions between clustering methods and can help selecting appropria...
Clustering analysis is a crucial part of pattern recognition, which refers to the procedure of patte...
This chapter deals with basic tools useful in clustering and classification and present some commonl...
In this paper a crossed clustering algorithm is proposed to partitioning a set of symbolic objects i...
Clustering seeks to group or to lump together objects or variables that share some observed qualitie...
This paper examines the problem of clustering a sequence of objects that cannot be described with a ...
International audienceOur main goal is to introduce three clustering functions based on the central ...