Results 71 to 80 of about 2,972 (114)

Analysis of Response Surface Designs to Outlier

2010 International Conference on E-Business and E-Government, 2010
Response surface designs investigating the effects of several factors have widely application and make the researcher or analyst to control the factors or model the effects of the input variables on the response of the process. Outliers among the measurements can almost be inevitable and will frequently have a highly confusing effect on response ...
Juntao Fang, Zhen He 0001
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Strategies for outlier analysis

IEE Two-day Colloquium on Knowledge Discovery and Data Mining, 1998
The handling of anomalous or outlying observations in a data set is one of the most important tasks in data pre-processing. It is important for three reasons. First, outlying observations can have a considerable influence on the results of an analysis.
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Outlier and influence diagnostics for meta-analysis

Research Synthesis Methods, 2010
The presence of outliers and influential cases may affect the validity and robustness of the conclusions from a meta-analysis. While researchers generally agree that it is necessary to examine outlier and influential case diagnostics when conducting a meta-analysis, limited studies have addressed how to obtain such diagnostic measures in the context of
Wolfgang, Viechtbauer, Mike W-L, Cheung
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Mobile Surveillance by 3D-Outlier Analysis

2011
We present a novel online method to model independent foreground motion by using solely traditional structure and motion (S+M) algorithms. On the one hand, the visible static scene can be reconstructed and on the other hand, the position and orientation (pose) of the observer (mobile camera) are estimated.
Peter Holzer, Axel Pinz
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Outlier detection in data envelopment analysis: an analysis of jackknifing

Journal of the Operational Research Society, 2002
Summary: This paper analyzes the resampling technique of jackknifing and its capability of detecting outliers in data envelopment analysis. It is well recognized that measured efficiency is sensitive to outliers; recent research has employed resampling techniques to estimate standard deviations in an attempt to handle outliers.
Jan Ondrich, John Ruggiero
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Purchasing Pattern of the Customers Based On Outliers Analysis

SSRN Electronic Journal, 2019
Data Mining (referred as extracting knowledge from data) is the process of discovering patterns, associations, and links in the huge stack of data which is based on the analysis done through different perspectives. There are many disciplines which are found under data mining some of them are clustering analysis, regression analysis, and classification ...
Rakhee Chhibber, Chetan Chadha
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Eliminating Outliers in Motion Occlusion Analysis

2000
Occlusion boundaries are considered either as outliers or as noise in most optical flow algorithms. In order to treat the boundary problem, many probabilistic algorithms like maximum likelihood [6] or expectation-maximization (EM) [17,3] decrease the weights of pixels in boundary regions gradually during estimation iterations. However, these approaches
Weichuan Yu, Konstantinos Daniilidis, Gerald Sommer   +2 more
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Application of outlier sample analysis

Proceedings of 2011 Cross Strait Quad-Regional Radio Science and Wireless Technology Conference, 2011
In order to optimize calibration set and increase prediction accuracy of the calibration model when near infrared spectroscopy was used to develop the model for rice amylose content, 18 abnormal spectrums produced by subjective and objective factors were eliminated based on Mahalanobis distance criterion combined with prediction concentration residual ...
null Xingang Xie, null Lijuan Shi
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An Introduction to Outlier Analysis

2012
Outliers are also referred to as abnormalities, discordants, deviants, or anomalies in the data mining and statistics literature. In most applications, the data is created by one or more generating processes, which could either reflect activity in the system or observations collected about entities.
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Analysis of Outliers with Adjusted Residuals

Technometrics, 1967
Many statistical procedures designed to guard against the occurrence of outliers or spurious observations in normal theory are based upon examining the magnitude of the residuals. A major difficulty involved is caused by the fact that the residuals are correlated.
G. C. Tiao, Irwin Guttman
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