Multivariate Decision Tree for Transformer Fault Diagnosis Based on Rough Set and Condition Entropy
Hongwen Yan · Computer and Information Technology · 2007
According to decision table's discernibility matrix in rough set theory,root attributes of multivariate decision tree can be selected.Using the theory of attribute reduction based on information entropy to select the node attribute and construct multivariate decision tree.The example shows that the multivariate decision tree model reduces the redundancy of fault diagnosis information,with high efficiency,and easy to be understood than univariate decision tree.