Combining machine learning and expert knowledge for classifying human posture
نویسندگان
چکیده
This paper presents a rule engine for classifying human posture according to information about the location of body parts. The rule engine was developed by enriching decision trees with expert knowledge. Results show 5 percentage points improvement in accuracy compared to support vector machines and a significant 11 percentage points compared to decision trees. The incorporation of expert knowledge overcomes the problem of classifier over-fitting observed with classifiers induced with machine learning. Better robustness of the posture classification rule engine is expected in real-life tests in comparison to classifiers induced with machine learning.
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تاریخ انتشار 2009