Generalization of an Outlier Model into a "Global" Perspective
Sponsor
This work is supported in part by Semiconductor Research Corporation projects 2012-TJ-2268, 2013-TJ-2466, and by National Science Foundation Grant No. 1255818.
Published In
2015 IEEE International Test Conference
Document Type
Citation
Publication Date
10-2015
Subjects
Outliers (Statistics), Automobiles -- Electronic equipment, Semiconductors -- Measurement
Abstract
n this work, we study the generalization of an outlier model from two perspectives, temporal and spatial. We show that model generalization with existing distribution-based outlier analysis methods can vary significantly. We then propose a “big data” outlier analysis approach together with a probability-based outlier evaluation for improving model generalization. Experiments are conducted based on two automotive product lines to explain the concepts and demonstrate the effectiveness of the proposed approach.
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Unaffiliated researchers can access the work here: http://dx.doi.org/10.1109/TEST.2015.7342396
DOI
10.1109/TEST.2015.7342396
Persistent Identifier
http://archives.pdx.edu/ds/psu/16645
Citation Details
Siatkowski, S., Chang, C. L., Wang, L. C., Sumikawa, N., Winemberg, L., & Daasch, W. R. (2015, October). Generalization of an outlier model into a "global" perspective. In Test Conference (ITC), 2015 IEEE International (pp. 1-10). IEEE.
Description
Appeared in 2015 IEEE International Test Conference, held Oct. 6-8, 2015, in Anaheim, CA. © Copyright 2016 IEEE - All rights reserved.