Add to ORKGIn this article, we study the notion of similarity within the context of cluster analysis. We begin by studying different distances commonly used for this task and highlight certain important properties that they might have, such as the use of data distribution or reduced sensitivity to the curse of dimen-sionality. Then we study inter- and intra-cluster similarities. We identify how the choices made can influence the nature of the clusters.
International audienceIn many domains, we face heterogeneous data with both numeric and categorical ...
Abstract: Clustering is the assignment of data objects (records) into groups (called clusters) so th...
In many algorithms in the field of data mining to perform clustering of given data, notion of ‘clust...
Clustering is an unsupervised learning technique which aims at grouping a set of objects into cluste...
Methods of data analysis and automatic processing are treated as knowledge discovery. In many cases ...
For using Data Mining, especially cluster analysis, one needs measures to determine the similarity o...
The problem of clustering consists in organizing a set of objects into groups or clusters, in a way ...
Similarity or distance measures are core components used by distance-based clustering algorithms to ...
This paper introduces a measure of similarity between two clusterings of the same dataset produced b...
The objective of this paper is to study cluster analysis to identify similarities. To enhance the ac...
Abstract The task of clustering is to identify classes of similar objects among a set of objects. Th...
In this paper, I describe a large variety of clustering methods within a single framework. This pape...
Abstract---- Clustering is process for finding similarity groups in data. It is considered as unsupe...
Grouping objects that are described by attributes, or clustering is a central notion in data mining....
Abstract. The unsupervised nature of cluster analysis means that objects can be clustered in many di...
International audienceIn many domains, we face heterogeneous data with both numeric and categorical ...
Abstract: Clustering is the assignment of data objects (records) into groups (called clusters) so th...
In many algorithms in the field of data mining to perform clustering of given data, notion of ‘clust...
Clustering is an unsupervised learning technique which aims at grouping a set of objects into cluste...
Methods of data analysis and automatic processing are treated as knowledge discovery. In many cases ...
For using Data Mining, especially cluster analysis, one needs measures to determine the similarity o...
The problem of clustering consists in organizing a set of objects into groups or clusters, in a way ...
Similarity or distance measures are core components used by distance-based clustering algorithms to ...
This paper introduces a measure of similarity between two clusterings of the same dataset produced b...
The objective of this paper is to study cluster analysis to identify similarities. To enhance the ac...
Abstract The task of clustering is to identify classes of similar objects among a set of objects. Th...
In this paper, I describe a large variety of clustering methods within a single framework. This pape...
Abstract---- Clustering is process for finding similarity groups in data. It is considered as unsupe...
Grouping objects that are described by attributes, or clustering is a central notion in data mining....
Abstract. The unsupervised nature of cluster analysis means that objects can be clustered in many di...
International audienceIn many domains, we face heterogeneous data with both numeric and categorical ...
Abstract: Clustering is the assignment of data objects (records) into groups (called clusters) so th...
In many algorithms in the field of data mining to perform clustering of given data, notion of ‘clust...