Classification and Prediction Method of Traditional Chinese Medicine Syndrome Based on Multi-label Learning and Bayesian Network
A technology of Bayesian network and multi-label learning, which is applied in the field of TCM clinical syndrome classification based on multi-label learning, can solve problems such as low accuracy rate, increased complexity, and low model generalization ability, achieving small increase , the effect of improving the accuracy rate
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[0024] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:
[0025]In order to better use the correlation between labels to improve the correct rate of classification, the present invention provides a classification method combining Bayesian network and multi-label learning. The method first makes statistics on the six common symptom types of TCM clinical diabetes, and uses the Bayesian network to calculate the conditional probability of each symptom type under the occurrence of other symptom types, and obtains a directed acyclic graph model among the six symptom types , this graphical model can well describe the correlation between markers: the arrows of two nodes represent whether the two symptoms are causal or unconditionally independent; and if there are no arrows connecting the variables in the nodes The two syndromes are said to be conditionally independent of each other. If two nodes are connected by a single arrow...
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