نتایج جستجو برای: wards method of clustering
تعداد نتایج: 21277414 فیلتر نتایج به سال:
the present study is paid to the evaluation of the welfare program of the unemployment insurance in iran. the main purpose which was the main reason for performing this thesis, was the unemployment insurance plan’s challenges in iran such as financial problems of this plan, prolongation of the credit receipt for some insured people, unemployment slow exiting from the unemployment insurance fund...
burnout is a response to the chronic work stress which is prevalent mostly among the people who do people job, like teaching. the purpose of this study was to develop a valid and reliable instrument that can measure burnout in foreign language teachers. although some widely used instruments were developed before which measured burnout in teachers, a specific instrument which include specific sy...
Clustering has been one of the main building blocks in the fields of machine learning and computer vision. Given a pair-wise distance measure, it is challenging to find a proper way to identify a subset of representative exemplars and its associated cluster structures. Recent trend on big data analysis poses a more demanding requirement on new clustering algorithm to be both scalable and accura...
The fuzzy c-means clustering algorithm is a useful tool for clustering; but it is convenient only for crisp complete data. In this article, an enhancement of the algorithm is proposed which is suitable for clustering trapezoidal fuzzy data. A linear ranking function is used to define a distance for trapezoidal fuzzy data. Then, as an application, a method based on the proposed algorithm is pres...
Image segmentation is an essential issue in image description and classification. Currently, in many real applications, segmentation is still mainly manual or strongly supervised by a human expert, which makes it irreproducible and deteriorating. Moreover, there are many uncertainties and vagueness in images, which crisp clustering and even Type-1 fuzzy clustering could not handle. Hence, Type-...
Spatial modelling was applied to self-reported schistosomiasis data from over 2.5 million school students from 12,399 schools in all regions of mainland Tanzania. The aims were to derive statistically robust prevalence estimates in small geographical units (wards), to identify spatial clusters of high and low prevalence and to quantify uncertainty surrounding prevalence estimates. The objective...
OBJECTIVE To compare the effect of two strategies (enhanced hand hygiene vs meticillin-resistant Staphylococcus aureus (MRSA) screening and decolonisation) alone and in combination on MRSA rates in surgical wards. DESIGN Prospective, controlled, interventional cohort study, with 6-month baseline, 12-month intervention and 6-month washout phases. SETTING 33 surgical wards of 10 hospitals in ...
Clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. K-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. In recent years, several algorithms are provided based on evolutionary algorithms for cluster...
In this work, a hierarchical ensemble of projected clustering algorithm for high-dimensional data is proposed. The basic concept of the algorithm is based on the active learning method (ALM) which is a fuzzy learning scheme, inspired by some behavioral features of human brain functionality. High-dimensional unsupervised active learning method (HUALM) is a clustering algorithm which blurs the da...
the wisdom of crowds, an innovative theory described in social science, claims that the aggregate decisions made by a group will often be better than those of its individual members if the four fundamental criteria of this theory are satisfied. this theory used for in clustering problems. previous researches showed that this theory can significantly increase the stability and performance of lea...
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