hierarchical agglomerative cluster analysis
Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol
... In this study we have used the open-source Python pack- age fastcluster (Müllner, 2013), which features several com- mon linkages. Of the included linkages the Ward, centroid and median linkages do not require the ...
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Use of cluster analysis technique for water quality assessment in mahitsy commune, central highland of madagascar
... and cluster analysis were used jointly to explore the water quality ...The hierarchical agglomerative cluster analysis classified the sampling points into three cluster ...
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An Approach for Cluster Analysis based upon Hierarchical Algorithm – Agglomerative Algorithm
... process[1].A cluster analysis plays big role in software ...categorization. Cluster analysis is used to separate the data into bunch or groups where no prior information is ...The ...
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Night Sky Brightness Assessment in Nigeria Using Environmetric and GIS Technique
... Cluster analysis is defined as the classification of data sets into groups with similar ...The Agglomerative Hierarchical Clustering method is recognized as a suitable method in the fields of ...
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An Agglomerative Hierarchical Clustering Algorithm for Labelling Morphs
... tive hierarchical clustering algorithm for labelling ...deeper analysis of seg- mentation results of a morphological seg- mentation ...proposed cluster- ing algorithm can capture allomorphs in ...
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Agglomerative Hierarchical Approach for Clustering Components of Similar Reusability
... A cluster analysis acts a big job in software development. Cluster analysis is the proposal for sorting out data into clusters or groups in a situation where no prior information about a ...
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Articles
... for cluster and ordination analysis (Appendix ...to analysis, as were characters that had missing values for the majority of ...the analysis. Phenograms were produced from classification ...
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A Comparative Analysis of Hierarchical Agglomerative Clustering and Distributed HAC
... The idea of DHAC is that for WSNs, the HAC algorithm does not actually need the global knowledge. To be specific, a node can make use of only one-hop neighbor knowledge for the computation. Nodes that are far apart will ...
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Knowledge Discovery in Medical Database using Machine Learning Techniques
... met. Agglomerative Hierarchical clustering was used to cluster the states by personnel information (number of doctors, community health workers, nurses and midwives), this was visualized using a ...
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MULTIVARIATE STATISTICS OF FERTILITY PARAMETER FLUXES IN CEMENT-DUST-POLLUTED SOILS IN MFAMOSING, NIGERIA: IMPACT ON AGRICULTURE
... correlation analysis (CA), principal component analysis (PCA), agglomerative hierarchical cluster analysis (AHCA) and multivariate analysis of co-variance (MANCOVA) were ...
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2011-IJCNN
... Once again the best result obtained by one scenario is marked as bold and its result is compared with the second best result, using the t-test statistical analysis. The best results which are statistically ...
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An Efficient and Effective Generic Agglomerative Hierarchical Clustering Approach
... In the context of non-parametric hierarchical clustering, one first group of papers, adopts a graph point of view of the clustering task. In particular, the nearest neighbors graph derived from the pairwise ...
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Hierarchical Cluster Analysis Histogram Thresholding with Local Minima
... using hierarchical cluster analysis" and "A Nonparametric Approach for Histogram Segmentation", we can eliminate disadvantages of Arifin method and keep merging and computing distance ...
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Modern Hierarchical, Agglomerative Clustering Algorithm Based on Various Widths
... substantial cluster whose size surpasses a client characterized edge (most extreme cluster estimate) will be isolated into various clusters utilizing a width that suits the thickness of that ...C. ...
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The influence of clustering techniques in the diagnosis of genetic disorders
... Clustering is a process of putting similar data into groups. Clustering has considered the most important unsupervised learning technique so, as every other problem of this kind; it deals with finding a structure in a ...
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Hierarchical Clustering for Identifying Crosscutting Concerns in Object Oriented Software Systems
... HACO is based on the idea of hierarchical agglom- erative clustering, and uses an heuristic for determin- ing the number of clusters. In order to determine the number k of clusters, we are focusing on determining ...
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A Study on Ranking of Atomic web Services Recommendation with Agglomerative Hierarchical Clustering
... services are emerging on the Internet. As a result, service-relevant data become too big to be efficiently processed by traditional approaches. Clustering is done automatically using agglomerative ...
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AHAC: Decision Tree Classification with Agglomerative Hierarchical Algorithm Clustering for Time Series Data Clustering
... The Agglomerative cluster group formation consists in training different classifiers with bootstrapped replicas of the original training data-set. That is, a new data-set is formed to train each classifier ...
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Clustering Analysis Using Hierarchy Grouping
... In this paper we consider different types of grouping using and testing various techniques. We explain in details and apply evident grouping, hierarchical grouping, and also agglomerative ...
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Hierarchical Latent Class Models for Cluster Analysis
... The task of learning HLC models is similar to the reconstruction of phylogenetic trees, which is a major topic in biological sequence analysis (Durbin et al., 1998). As a matter of fact, phylogenetic trees are ...
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