DocumentCode
2591118
Title
Improving classification with boundary instances multiplier algorithm based on IF-THEN rules
Author
Muntean, Maria ; Ileana, Ioan ; Valean, Honoriu
Author_Institution
Dept. of Sci. & Eng., 1 Decembrie 1918 Univ. of Alba Iulia, Alba Iulia, Romania
fYear
2012
fDate
24-27 May 2012
Firstpage
272
Lastpage
277
Abstract
Classification of sensory data is a major research problem in Wireless Sensor Networks (WSNs) and it can be widely used in reducing the data transmission in WSNs and also in process monitoring. Because the task of classification must be as accurate as possible, the paper proposes a novel method based IF-THEN rules to enhance the overall accuracy. The results demonstrate that the proposed approach is also significant to improve the true positive accuracy of imbalanced datasets.
Keywords
data mining; pattern classification; BIMA; IF-THEN rules; WSN; boundary instances multiplier algorithm; data transmission reduction; imbalanced datasets; process monitoring; sensory data classification; true positive accuracy improvement; wireless sensor networks; Accuracy; Classification algorithms; Monitoring; Temperature measurement; Temperature sensors; Training; Wireless sensor networks; IF-THEN rules; accuracy; classification; imbalanced data;
fLanguage
English
Publisher
ieee
Conference_Titel
Automation Quality and Testing Robotics (AQTR), 2012 IEEE International Conference on
Conference_Location
Cluj-Napoca
Print_ISBN
978-1-4673-0701-7
Type
conf
DOI
10.1109/AQTR.2012.6237716
Filename
6237716
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