Add to ORKGAbstract: In data mining, efforts have focused on finding methods for efficient and effective cluster analysis in large databases. Active themes of research focus on the scalability of clustering methods, the effectiveness of methods for clustering complex shapes and types of data, high-dimensional clustering techniques, and methods for clustering mixed numerical and categorical data in large databases. One of the most accuracy approach based on dynamic modeling of cluster similarity is called Chameleon. In this paper we present a modified hierarchical clustering algorithm that used the main idea of Chameleon and the effectiveness of suggested approach will be demonstrated by the experimental results.
ABSTRACT Clustering and visualizing high dimensional dynamic data is a challenging problem in the da...
Abstract: A fundamental and difficult problem in cluster analysis is the determination of the “true...
We survey agglomerative hierarchical clustering algorithms and discuss efficient implementations tha...
Clustering in data mining is a discovery process that groups a set of data such that the intracluste...
Clustering is a process of grouping objects and data into groups of clusters to ensure that data obj...
<p>In this work results of modified Chameleon algorithm are discussed. Hierarchical multilevel algor...
The objective of data mining is to take out information from large amounts of data and convert it in...
In data mining, efforts have focused on finding methods for efficient and effective cluster analysis...
Abstract — Clustering techniques have a wide use and importance nowadays. This importance tends to i...
In this paper, we propose a parameter-insensitive data partitioning approach for Chameleon, a hierar...
We survey agglomerative hierarchical clustering algorithms and discuss efficient implementations tha...
In this paper, we propose a parameter-insensitive data partitioning approach for Chameleon, a hierar...
Clustering aims to differentiate objects from different groups (clusters) by similarities or distanc...
Data Clustering is defined as grouping together objects which share similar properties. These proper...
Knowledge discovery in databases is the non-trivial process of identifying valid, novel potentially ...
ABSTRACT Clustering and visualizing high dimensional dynamic data is a challenging problem in the da...
Abstract: A fundamental and difficult problem in cluster analysis is the determination of the “true...
We survey agglomerative hierarchical clustering algorithms and discuss efficient implementations tha...
Clustering in data mining is a discovery process that groups a set of data such that the intracluste...
Clustering is a process of grouping objects and data into groups of clusters to ensure that data obj...
<p>In this work results of modified Chameleon algorithm are discussed. Hierarchical multilevel algor...
The objective of data mining is to take out information from large amounts of data and convert it in...
In data mining, efforts have focused on finding methods for efficient and effective cluster analysis...
Abstract — Clustering techniques have a wide use and importance nowadays. This importance tends to i...
In this paper, we propose a parameter-insensitive data partitioning approach for Chameleon, a hierar...
We survey agglomerative hierarchical clustering algorithms and discuss efficient implementations tha...
In this paper, we propose a parameter-insensitive data partitioning approach for Chameleon, a hierar...
Clustering aims to differentiate objects from different groups (clusters) by similarities or distanc...
Data Clustering is defined as grouping together objects which share similar properties. These proper...
Knowledge discovery in databases is the non-trivial process of identifying valid, novel potentially ...
ABSTRACT Clustering and visualizing high dimensional dynamic data is a challenging problem in the da...
Abstract: A fundamental and difficult problem in cluster analysis is the determination of the “true...
We survey agglomerative hierarchical clustering algorithms and discuss efficient implementations tha...