SAX Breakpoints for Random Forest Based Real-Time Contrast Control Chart

Authors

  • In-Seok Lee Korea University
  • Jun-Geol Baek Korea University

DOI:

https://doi.org/10.1609/aaai.v33i01.33019959

Abstract

In the manufacturing process, process monitoring is very important. Real-time contrast (RTC) control chart outperforms existing monitoring methods. However, the performance of RTC control chart depends on the classifier. The existing RTC charts use random forest (RF), support vector machine (SVM), or kernel linear discriminant analysis (KLDA) as a classifier. RF classifier can find cause of faults but the performance is lower than others. Therefore, we suggest the data representation method to improve the RF based RTC control chart. Symbolic aggregate approximation (SAX) is famous method to improve the performance of classification and clustering. We convert the input data by using SAX. We change the parameters of SAX such as alphabet size and breakpoints to improve the performance. Experiment shows that represented data is efficient method to improve the performance of RTC control chart.

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Published

2019-07-17

How to Cite

Lee, I.-S., & Baek, J.-G. (2019). SAX Breakpoints for Random Forest Based Real-Time Contrast Control Chart. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 9959-9960. https://doi.org/10.1609/aaai.v33i01.33019959

Issue

Section

Student Abstract Track