Control chart pattern recognition using semi-supervised learning
Miin‐Shen Yang, Jenn-Hwai Yang · 2007
This paper presents a semi-supervised learning algorithm for a control chart pattern recognition system. A learning neural network is trained with labeled control chart patterns based on unsupervised learning. We then use the classification method based on a statistical correlation coefficient approach to test patterns. We find that the proposed semi-supervised learning algorithm is effective according to numerical comparisons.