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ESEM
2007
ACM
13 years 8 months ago
An Approach to Outlier Detection of Software Measurement Data using the K-means Clustering Method
The quality of software measurement data affects the accuracy of project manager’s decision making using estimation or prediction models and the understanding of real project st...
Kyung-A Yoon, Oh-Sung Kwon, Doo-Hwan Bae
ICDM
2006
IEEE
226views Data Mining» more  ICDM 2006»
14 years 9 days ago
Converting Output Scores from Outlier Detection Algorithms into Probability Estimates
Current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. We argue that converting the scores into wel...
Jing Gao, Pang-Ning Tan
CIKM
2007
Springer
14 years 13 days ago
Detecting distance-based outliers in streams of data
In this work a method for detecting distance-based outliers in data streams is presented. We deal with the sliding window model, where outlier queries are performed in order to de...
Fabrizio Angiulli, Fabio Fassetti
IPPS
2008
IEEE
14 years 20 days ago
Outlier detection in performance data of parallel applications
— When an adaptive software component is employed to select the best-performing implementation for a communication operation at runtime, the correctness of the decision taken str...
Katharina Benkert, Edgar Gabriel, Michael M. Resch
CVPR
2005
IEEE
13 years 12 months ago
Linear Combination Representation for Outlier Detection in Motion Tracking
In this paper we show that Ullman and Basri’s linear combination (LC) representation, which was originally proposed for alignment-based object recognition, can be used for outli...
Guodong Guo, Charles R. Dyer, Zhengyou Zhang