Agglomerative Hierarchical Clustering Algorithm- A Review
نویسندگان
چکیده
Clustering is a task of assigning a set of objects into groups called clusters. In data mining, hierarchical clustering is a method of cluster analysis which seeks to build a hierarchy of clusters. Strategies for hierarchical clustering generally fall into two types:Agglomerative: This is a "bottom up" approach: each observation starts in its own cluster, and pairs of clusters are merged as one moves up the hierarchy.Divisive: This is a "top down" approach: all observations start in one cluster, and splits are performed recursively as one moves down the hierarchy.
منابع مشابه
2 Review of Agglomerative Hierarchical Clustering Algorithms
Hierarchical methods are well known clustering technique that can be potentially very useful for various data mining tasks. A hierarchical clustering scheme produces a sequence of clusterings in which each clustering is nested into the next clustering in the sequence. Since hierarchical clustering is a greedy search algorithm based on a local search, the merging decision made early in the agglo...
متن کاملImplementing Agglomerative hierarchical clustering using multiple attribute
Agglomerative hierarchical clustering algorithm used with top down approach. It implement with multiple attributes. In multiple attributes frequency calculation is allocated. Memory requirements are less in this process. Hierarchical clustering produce accurate result than any other algorithm. This is very less time consuming process.
متن کاملMethods of Hierarchical Clustering
We survey agglomerative hierarchical clustering algorithms and discuss efficient implementations that are available in R and other software environments. We look at hierarchical self-organizing maps, and mixture models. We review grid-based clustering, focusing on hierarchical density-based approaches. Finally we describe a recently developed very efficient (linear time) hierarchical clustering...
متن کاملMultiDendrograms: Variable-Group Agglomerative Hierarchical Clusterings
MultiDendrograms is a Java-written application that computes agglomerative hierarchical clusterings of data. Starting from a distances (or weights) matrix, MultiDendrograms is able to calculate its dendrograms using the most common agglomerative hierarchical clustering methods. The application implements a variable-group algorithm that solves the non-uniqueness problem found in the standard pai...
متن کاملMultilevel Refinement for Hierarchical Clustering
Hierarchical methods are well known clustering technique that can be potentially very useful for various data mining tasks. A hierarchical clustering scheme produces a sequence of clusterings in which each clustering is nested into the next clustering in the sequence. Since hierarchical clustering is a greedy search algorithm based on a local search, the merging decision made early in the agglo...
متن کاملAgglomerative Clustering of Bagged Data Using Joint Distributions
Current methods for hierarchical clustering of data either operate on features of the data or make limiting model assumptions. We present the hierarchy discovery algorithm (HDA), a model-based hierarchical clustering method based on explicit comparison of joint distributions via Bayesian network learning for predefined groups of data. HDA works on both continuous and discrete data and offers a ...
متن کامل