SENSITIVITY-BASED INFORMATION SELECTION FOR PREDICTING INDIVIDUAL'S SUB-HEALTH ON TCM DOCTORS' DIAGNOSIS DATA

Abstract

In this paper we propose an approach of predicting individual's sub-health based on the principle of TCM as a preventive medicine. The object's vision features like features of tongue, eye and face are extracted for modeling a process of TCM doctor's diagnosis. Because of the diversity and uncertainty of TCM doctors' diagnosis, the sensitivity is defined as a criterion to select the training data from the derived features and the diagnosis data given by different TCM doctors for constructing the sub-health inference model. The experiment results show that the sensitivity-based data selection improves the model's inference performance on the accuracy, correlation and residual variance.