scholarly journals Applied Hierarchical Cluster Analysis with Average Linkage Algoritm

CAUCHY ◽  
2017 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Cindy Cahyaning Astuti ◽  
Rahmania Sri Untari

This research was conducted in Sidoarjo District where source of data used from secondary data contained in the book <em>"Kabupaten Sidoarjo Dalam Angka 2016"</em> .In this research the authors chose 12 variables that can represent sub-district characteristics in Sidoarjo. The variable that represents the characteristics of the sub-district consists of four sectors namely geography, education, agriculture and industry. To determine the equitable geographical conditions, education, agriculture and industry each district, it would require an analysis to classify sub-districts based on the sub-district characteristics. Hierarchical cluster analysis is the analytical techniques used to classify or categorize the object of each case into a relatively homogeneous group expressed as a cluster. The results are expected to provide information about dominant sub-district characteristics and non-dominant sub-district characteristics in four sectors based on the results of the cluster is formed.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 4866-4866
Author(s):  
Akos Czibere ◽  
Christian Prall ◽  
Ulrich Steidl ◽  
Ingmar Bruns ◽  
Andrea Kuendgen ◽  
...  

Abstract The biology of myelodysplastic syndromes (MDS) is reflected in aberrant transcription levels of the myeloid lineage. It was the purpose of this study to provide potential novel therapeutic targets by identifying molecular alterations that are pertinent to myelodysplastic syndromes. cDNA from bone marrow-derived CD34+ hematopoietic stem and progenitor cells from 6 healthy persons, and 16 patients with MDS (Table 1) was hybridized to cDNA arrays comprising 1185 well-characterized genes. We used the complete cDNA array expression values to build a dendrogram including all samples under investigation. Interestingly, patient survival had a striking impact on our gene signature for it was the parameter that had the strongest statistical association with the segregation of our MDS patients into 2 sub clusters (Figure 1). We examined whether this segregation of MDS patients was associated with age, gender, MDS-type according to FAB, WHO, IPSS, karyotype or survival. We determined correlation coefficients and found “survival” to be the parameter with the strongest statistically significant association with the segregation of MDS patients into 2 sub clusters (Spearman = 0.697, P = 0.003). The WHO type was less significantly associated (Spearman = 0.537, P = 0.032), and the FAB type did not reach statistical significance (Spearman = 0.492, P = 0.053). Transcriptional changes that are associated with short survival may also indicate to potential novel therapeutic targets. Since median age of patients with MDS is 70 at diagnosis, the majority of patients are not suitable for therapies that are not well tolerated. Moreover, some patients have a nearly normal life expectancy. Ideally, new therapeutic agents should, therefore, be tailored for patients with short survival and be well-tolerated like e.g. Bevacizumab and Cetuximab. But, we could not find increased expression of Bevacizumab and Cetuximab related EGFR- or VEGFR-target genes in CD34+ cells from MDS patients with short survival. In sum, there are transcriptional alterations that are strongly associated with short survival, and thus valuable for prognostication of patients with MDS. Table 1. Classification, and karyotypes of patients with MDS who were analyzed by means of cDNA array analysis Patient No. Age/ Sex FAB (a) IPSS (b) WHO (c) Karyotype (a) FAB, French-American-British cooperative group classification, (b) IPSS, international prognostic scoring system; int, intermediate, (c) WHO, World Health Organization classification 1 61/ F RA int-I RCMD 46, XX, 13q- 2 68/ F RA int-I 5q- 46, XX, 5q-, 12p- 3 62/ M RA int-I RCMD 47, XY, +8 4 50/ M RA int-I RCMD 46, XY, t(X;1) 5 18/ F RA low PRA 46, XX 6 51/ M RA low RCMD 46, XY 7 51 /F RA int-I 5q- 46, XX, 5q-, 12p 8 75/ M RAEB high RAEB II 46, XY, 7q- 9 79/ M RAEB-t high sAML complex 10 68/ M RAEB int-II RAEB-II 46, XY 11 70/ F RAEB-t high sAML 46, XX, 15q- 12 52/ M RAEB-t high sAML complex 13 72/ M RAEB-t high sAML complex 14 75/ M RAEB int-I RAEB-I 46, XY 15 72/ M sAML/MDS - sAML complex 16 76/ M sAML/MDS - sAML 46, XY Dendrogram derived from hierarchical cluster analysis using the 1-correlation distance metrics and an average linkage algorithm. Dendrogram derived from hierarchical cluster analysis using the 1-correlation distance metrics and an average linkage algorithm.


2017 ◽  
Vol 7 (2) ◽  
pp. 76
Author(s):  
Ferry Kondo Lembang ◽  
Patresya Yulita Lessil ◽  
Salmon Notje Aulele

Regional gross domestic product is one of the important indicators to determine economic conditions in an area. Therefore it is very interesting to discuss and to determine the economic progress of a region. Cluster anlysis aims to classify objects based on the characteristics into cluster that have the properties that are relatively similar and clearly distinguish between one cluster agains another. The main objective of the research that classifies 33 provinces based on the value of regional gross domestic product at constant price in 2013 using hierarchical cluster analysis for average linkage method. The results showed that the cluster were carried out on 33 provinces in Indonesia formed 3 cluster with details of that cluster 1 consisting of Sumatera, Kalimantan, Sulawesi, Nusa Tenggara, Bali, Papua, Maluku and Jawa Tengah, DI Yogyakarta, and Banten, cluster 2 consisting of 1 provinces of DKI Jakarta and cluster 3 which consists of 2 provinces namely Jawa Barat dan Jawa Timur.


Author(s):  
Jianwei Bu ◽  
Wei Liu ◽  
Zhao Pan ◽  
Kang Ling

Traditional methods for hydrochemical analyses are effective but less diversified, and are constrained to limited objects and conditions. Given their poor accuracy and reliability, they are often used in complement or combined with other methods to solve practical problems. Cluster analysis is a multivariate statistical technique that extracts useful information from complex data. It provides new ideas and approaches to hydrogeochemical analysis, especially for groundwater hydrochemical classification. Hierarchical cluster analysis is the most widely used method in cluster analysis. This study compared the advantages and disadvantages of six hierarchical cluster analysis methods and analyzed their objects, conditions, and scope of application. The six methods are: The single linkage, complete linkage, median linkage, centroid linkage, average linkage (including between-group linkage and within-group linkage), and Ward’s minimum-variance. Results showed that single linkage and complete linkage are unsuitable for complex practical conditions. Median and centroid linkages likely cause reversals in dendrograms. Average linkage is generally suitable for classification tasks with multiple samples and big data. However, Ward’s minimum-variance achieved better results for fewer samples and variables.


Author(s):  
Milan Radojicic ◽  
Aleksandar Djokovic ◽  
Nikola Cvetkovic

Unpredictable and uncontrollable situations have happened throughout history. Inevitably, such situations have an impact on various spheres of life. The coronavirus disease 2019 has affected many of them, including sports. The ban on social gatherings has caused the cancellation of many sports competitions. This paper proposes a methodology based on hierarchical cluster analysis (HCA) that can be applied when a need occurs to end an interrupted tournament and the conditions for playing the remaining matches are far from ideal. The proposed methodology is based on how to conclude the season for Serie A, a top-division football league in Italy. The analysis showed that it is reasonable to play 14 instead of the 124 remaining matches of the 2019–2020 season to conclude the championship. The proposed methodology was tested on the past 10 seasons of the Serie A, and its effectiveness was confirmed. This novel approach can be used in any other sport where round-robin tournaments exist.


2010 ◽  
Vol 41 (2) ◽  
pp. 126-133 ◽  
Author(s):  
N. Kalamaras ◽  
H. Michalopoulou ◽  
H. R. Byun

In this study a method proposed by Byun & Wilhite, which estimates drought severity and duration using daily precipitation values, is applied to data from stations at different locations in Greece. Subsequently, a series of indices is calculated to facilitate the detection of drought events at these sites. The results provide insight into the trend of drought severity in the region. In addition, the seasonal distribution of days with moderate and severe drought is examined. Finally, the Hierarchical Cluster Analysis method is used to identify sites with similar drought features.


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