نتایج جستجو برای: outlier detection
تعداد نتایج: 569959 فیلتر نتایج به سال:
Frequent pattern outlier factor is used to detect outliers with complete frequent itemsets. But it is difficult in real-world time-series data streams application because of its low efficiency. In this paper, we propose a novel maximal frequent pattern outlier factor (MFPOF) and an outlier detection algorithm (OODFP) for online high-dimensional time-series outlier detection. Firstly, the time-s...
Outlier detection statistics based on two models, the case-deletion model and the mean-shift model, are developed in the context of a multivariate linear regression model. These are generalizations of the univariate Cook’s distance and other diagnostic statistics. Approximate distributions of the proposed statistics are also obtained to get suitable cutoff points for significance tests. In addi...
In many applications, stream data are too voluminous to be collected in a central fashion and often transmitted on a distributed network. In this paper, we focus on the outlier detection over distributed data streams in real time, firstly, we formalize the problem of outlier detection using the kernel density estimation technique. Then, we adopt the fading strategy to keep pace with the transie...
The majority of data sets contain observations that do not conform to the structure followed by the rest of the data. These observations, known as outliers, can be found using a multitude of statistical and non-statistical methods. This paper highlights a generalized system built, specifically for price index surveys, which analysts can use to test different outlier detection methods. It also d...
A wireless sensor network consist of large number of nodes that possesses very small battery life and data processing capabilities but these microelectronics system are capable of measuring physical and various environment related consequences like sound, pressure, motion, pollution causing agents etc. In this paper we will review the basics of wireless sensor network and outlier in the wireles...
The problem of outlier detection has been studied in the context of several domains and has received attention from the database research community. To the best of our knowledge, work up to date focuses exclusively on the problem as follows [1]: “given a single set of observations in some space, find those that deviate so as to arouse suspicion that they were generated by a different mechanism....
In a binary response regression model, classical residuals are diicult to deene and interpret due to the discrete nature of the response variable. In contrast , Bayesian residuals have continuous-valued posterior distributions which can be graphed to learn about outlying observations. Two deenitions of Bayesian residuals are proposed for binary regression data. Plots of the posterior distributi...
In the field of wireless sensor networks, the measurements that deviate from the normal behaviour of sensed data are taken to be as outliers. The potential sources of outliers can be noise and errors, events, and malicious attacks on the network. This paper give an overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Also, a technique-based ...
Data mining provides a way for finding hidden and useful knowledge from the large amount of data .usually we find any information by finding normal trends or distribution of data .But sometimes rare event or data object may provide information which is very interesting to us .Outlier detection is one of the task of data mining .It finds abnormal data point or sequence hidden in the dataset .Dat...
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