Add to ORKGThis paper presents an approach to calculate the dissimilarity between probabilistic symbolic objects. The proposed dissimilarity measure is based on both a comparison function and an aggregation function. Comparison function is a proximity coefficient based on statistical information given by each probabilistic elementary event. The aggregation function is a proximity index, related to Minkowski measure, which aggregates the results given by comparison functions
AbstractDeciding whether one probability distribution is more informative (in the sense of represent...
We discuss definitions and properties of similarity and dissimilarity coefficients, including their ...
This paper defines the notion of analogical dissimilarity between four objects, with a special focus...
This paper presents an approach to calculate the dissimilarity between probabilistic symbolic object...
The aim of this paper consists in showing the building of dissimilarity measures between either Bool...
Symbolic data analysis generalizes some standard statistical data mining methods, such as those deve...
A successful attempt in exploring a dissimilarity measure which captures the reality is made in this...
In the present work, a new weighted measure of dissimilarity between two probability distributions i...
Abstract-The measures of dissimilarity between basic belief assignments (bba’s) in the framework of ...
We present a new mathematical notion, dissimilarity function, and based on it, a radical extension o...
In this paper, a novel similarity measure for estimating the degree of similarity between two patter...
We propose a novel hierarchical clustering for distribution valued dissimilarities. Analysis of larg...
Clustering is the process of grouping a set ofphysical or abstract objects into classes of similarob...
Abstract We deal with methods for analyzing complex structured data, especially, distribution valued...
In this paper a dissimilarity index between statistical populations is pro-posed without the hypothe...
AbstractDeciding whether one probability distribution is more informative (in the sense of represent...
We discuss definitions and properties of similarity and dissimilarity coefficients, including their ...
This paper defines the notion of analogical dissimilarity between four objects, with a special focus...
This paper presents an approach to calculate the dissimilarity between probabilistic symbolic object...
The aim of this paper consists in showing the building of dissimilarity measures between either Bool...
Symbolic data analysis generalizes some standard statistical data mining methods, such as those deve...
A successful attempt in exploring a dissimilarity measure which captures the reality is made in this...
In the present work, a new weighted measure of dissimilarity between two probability distributions i...
Abstract-The measures of dissimilarity between basic belief assignments (bba’s) in the framework of ...
We present a new mathematical notion, dissimilarity function, and based on it, a radical extension o...
In this paper, a novel similarity measure for estimating the degree of similarity between two patter...
We propose a novel hierarchical clustering for distribution valued dissimilarities. Analysis of larg...
Clustering is the process of grouping a set ofphysical or abstract objects into classes of similarob...
Abstract We deal with methods for analyzing complex structured data, especially, distribution valued...
In this paper a dissimilarity index between statistical populations is pro-posed without the hypothe...
AbstractDeciding whether one probability distribution is more informative (in the sense of represent...
We discuss definitions and properties of similarity and dissimilarity coefficients, including their ...
This paper defines the notion of analogical dissimilarity between four objects, with a special focus...