نتایج جستجو برای: مدلaggregate with outlier

تعداد نتایج: 9193822  

ژورنال: :محیط شناسی 2010
پرستو پریور احمد رضا یاوری شهرزاد فریادی احد ستوده

افت کیفیت محیط زیست شهر تهران در چند دهة اخیر باعث شده است این شهر همواره در صدر آلوده ترین کلانشهرهای دنیا قرار گیرد. رشد سریع جمعیت، گسترش شهرنشینی و در نتیجه تغییرات زیاد کاربری ها و پوشش اراضی سبب تخریب شدید بنیان های اکولوژیکی سرزمین، کاهش ظرفیت جذب آلودگی ها و در نتیجه تشدید آلودگی ها در این شهر شده است. در این تحقیق، با استفاده از رهیافتی جامع نگر و فرایند گرا که تمرکز اصلی آن بر روابط س...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه علامه طباطبایی - دانشکده اقتصاد 1389

this thesis is a study on insurance fraud in iran automobile insurance industry and explores the usage of expert linkage between un-supervised clustering and analytical hierarchy process(ahp), and renders the findings from applying these algorithms for automobile insurance claim fraud detection. the expert linkage determination objective function plan provides us with a way to determine whi...

Journal: :IEEE Transactions on Knowledge and Data Engineering 2021

Cluster analysis and outlier detection are two continuously rising topics in data mining area, which fact connect to each other deeply. structure is vulnerable outliers; inversely, outliers the points belonging none of any clusters. Unfortunately, most existing studies do not notice coupled relationship between these tasks handle them separately. In this article, we consider joint cluster probl...

اکبر بیگلریان, , غلامرضا بابایی, , فیروز امانی, , مریم کشاورز, ,

Background: An outlier is an observation that lies an abnormal distance from other values in a random sample from a population. Outliers sometimes deal with to abnormality in obtained results from collected data and information. known outlier data by researchers, physicians and other persons that work in medical fields and sciences is important and they must control data before getting result a...

ژورنال: پژوهش های ریاضی 2022

Multivariate time series data, often, modeled using vector autoregressive moving average (VARMA) model. But presence of outliers can violates the stationary assumption and may lead to wrong modeling, biased estimation of parameters and inaccurate prediction. Thus, detection of these points and how to deal properly with them, especially in relation to modeling and parameter estimation of VARMA m...

Journal: :CoRR 2018
Hongfu Liu Jun Li Yue Wu Yun Fu

Cluster analysis and outlier detection are strongly coupled tasks in data mining area. Cluster structure can be easily destroyed by few outliers; on the contrary, the outliers are defined by the concept of cluster, which are recognized as the points belonging to none of the clusters. However, most existing studies handle them separately. In light of this, we consider the joint cluster analysis ...

Journal: :Journal of the American Statistical Association 1976

2013
Oyvind Bjertnaes Kjersti Eeg Skudal Hilde Hestad Iversen

BACKGROUND A general trend towards positive patient-reported evaluations of hospitals could be taken as a sign that most patients form a homogeneous, reasonably pleased group, and consequently that there is little need for quality improvement. The objective of this study was to explore this assumption by identifying and statistically validating clusters of patients based on their evaluation of ...

2014
Djoko Budiyanto Setyohadi Azuraliza Abu Bakar Zulaiha Ali Othman

Many studies of outlier detection have been developed based on the cluster-based outlier detection approach, since it does not need any prior knowledge of the dataset. However, the previous studies only regard the outlier factor computation with respect to a single point or a small cluster, which reflects its deviates from a common cluster. Furthermore, all objects within outlier cluster are as...

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