نتایج جستجو برای: an agglomerative hierarchical cluster analysis with ward
تعداد نتایج: 12034616 فیلتر نتایج به سال:
Clustering ensemble performance is affected by two main factors: diversity and quality. Selection of a subset of available ensemble members based on diversity and quality often leads to a more accurate ensemble solution. However, there is not a certain relationship between diversity and quality in selection of subset of ensemble members. This paper proposes the Hierarchical Cluster Ensemble Sel...
We propose a hybrid clustering method, Hierarchical Ordered Partitioning And Collapsing Hybrid (HOPACH), which is a hierarchical tree of clusters. The methodology combines the strengths of both partitioning and agglomerative clustering methods. At each node, a cluster is partitioned into two or more smaller clusters with an enforced ordering of the clusters. Collapsing steps uniting the two clo...
BACKGROUND Vulvodynia classification is based on the sensory dimensions of pain and does not include psychological factors associated with the pain experience and treatment outcomes. Previous work has shown that individuals with chronic pain can be classified into subgroups based on pain sensitivity, psychological distress, mood, and symptom severity. OBJECTIVE The aim of this study was to id...
Abstract The vast majority of the existing social network-based group decision-making models require extra information such as trust/distrust, influence and so on. However, in practical process, it is difficult to get additional apart from opinions decision makers. For large-scale making (LSGDM) problem which makers articulate their preferences form comparative linguistic expressions, this pape...
Disambiguating person names in a set of documents (such as a set of web pages returned in response to a person name) is a key task for the presentation of results and the automatic profiling of experts. With largely unstructured documents and an unknown number of people with the same name the problem presents many difficulties and challenges. This chapter treats the task of person name disambig...
This paper presents algorithms for hierarchical, agglomerative clustering which perform most efficiently in the general-purpose setup that is given in modern standard software. Requirements are: (1) the input data is given by pairwise dissimilarities between data points, but extensions to vector data are also discussed (2) the output is a “stepwise dendrogram”, a data structure which is shared ...
Clustering is a data mining technique for the analysis of data in various areas such as pattern recognition, image processing, information science, bioinformatics etc. Hierarchical clustering techniques form the clusters based on top-down and bottom-up approaches. Hierarchical agglomerative clustering is a bottom-up clustering method. Ant based clustering methods form clusters by picking and dr...
based on the latest records of typhlops vermicularis merrem, 1820 from iran, this species is distributed in the northern and southern regions of the country. in this study, new records of typhlops vermicularis are presented and it is shown that distribution range of this species is extended towards the eastern and western iran, and according to the new distribution map, it can be assumed that t...
Agglomerative hierarchical clustering methods based on Gaussian probability models have recently shown promise in a variety of applications. In this approach, a maximum-likelihood pair of clusters is chosen for merging at each stage. Unlike classical methods, model-based methods reduce to a recurrence relation only in the simplest case, which corresponds to the classical sum of squares method. ...
Background and Objective: Using proteomic methodologies and advent of high-throughput (HTP) investigation of proteins has created a need for new approaches in bioinformatics analysis of experimental results. Cluster analysis is a suitable statistical procedure that can be useful for analyzing these data sets. Materials and Methods: In this research study, the identified proteins associated wi...
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