Control chart pattern recognition using semi-supervised learning
نویسنده
چکیده
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. Key-Words: Control chart; Pattern recognition; Semi-supervised learning; Labeled pattern; Recognition rate.
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