Results 31 to 40 of about 245,542 (303)
Gibbs sampling will fail in outlier problems with strong masking [PDF]
, 1995 This paper discusses the convergence of the Gibbs sampling algorithm when it is applied to the problem of outlier detection in regression models. Given any vector of initial conditions, theoretically, the algorithm converges to the true posterior ...
Justel, Ana, Peña, Daniel
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Current Biology, 2013 SummaryReports of photographic memory are widespread but the search for truly extraordinary memory abilities has uncovered only a handful of examples. But the fact that such individuals exist has fascinated and begs the question, what is the source of such abilities? Cyrus Martin reports.
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Subspace Approximation with Outliers [PDF]
, 2020 The subspace approximation problem with outliers, for given $n$ points in $d$ dimensions $x_{1},\ldots, x_{n} \in R^{d}$, an integer $1 \leq k \leq d$, and an outlier parameter $0 \leq α\leq 1$, is to find a $k$-dimensional linear subspace of $R^{d}$ that minimizes the sum of squared distances to its nearest $(1-α)n$ points.
Amit Deshpande 0001, Rameshwar Pratap
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Advancements of Outlier Detection: A Survey [PDF]
, 2013 Outlier detection is an important research problem in data mining that aims to discover useful abnormal and irregular patterns hidden in large datasets. In this paper, we present a survey of outlier detection techniques to reflect the recent advancements
Zhang, Ji, Ji Zhang
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Robust tests for testing the parameters of a normal population [PDF]
Journal of Sciences, Islamic Republic of Iran, 2014 This article aims to provide a simple robust method to test the parameters of a normal population by using the new diagnostic tool called the “Forward Search” (FS) method.
A. Mahdavi, M. Towhidi
doaj
THE USE OF STATISTICAL CRITERIA FOR EVALUATION TEST OF DATA ON PROPERTIES OF INORGANIC SUBSTANCES
Тонкие химические технологии, 2017 Three statistical criteria were compared on the basis of the sampling of chemical data in the article. When the criteria were compared, the level of significance was taken as equal to 0.05, because this value is most often used in the technical ...
I. D. Tarasenko, V. A. Dudarev
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OUTLIER DETECTION TECHNIQUE USING CT-OCSVM AND FUZZY RULE-BASED SYSTEM IN WIRELESS SENSOR NETWORKS
Journal of Engineering and Sustainable Development, 2020 The development of Wireless Sensor Networks (WSNs) has been attained in the past few years due to its important using in wide range of application. The readings of data derived from WSN nodes are not always accurate and may contain abnormal data.
Hussein Hassan Shia +2 more
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Scheduling with Outliers [PDF]
, 2009 23 pages, 3 ...
Anupam Gupta 0001 +3 more
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Context-aware Adaptive Outlier Detection in Trajectory Data
, 2020 With the advent of data mining and business processes automation, outlier detection has evolved into a major problem attracting significant research in relation to several application domains.
Wenbin Zhang +9 more
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Weighted fast-trimmed likelihood estimator for mixture regression models
Frontiers in Applied Mathematics and StatisticsThe fast-trimmed likelihood estimate is a robust method to estimate the parameters of a mixture regression model. However, this method is vulnerable to the presence of bad leverage points, which are outliers in the direction of independent variables.
Hassan S. Uraibi, Mohammed Qasim Waheed
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