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
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;
Conference_Titel :
Automation Quality and Testing Robotics (AQTR), 2012 IEEE International Conference on
Conference_Location :
Cluj-Napoca
Print_ISBN :
978-1-4673-0701-7
DOI :
10.1109/AQTR.2012.6237716
