Analysis of Hepatitis Dataset by Decision Tree Graph-Based Induction
نویسندگان
چکیده
We analyzed the hepatitis data by Decision Tree GraphBased Induction (DT-GBI), which constructs a decision tree for graphstructured data while simultaneously constructing attributes for classification. An attribute at each node in the decision tree is a discriminative pattern (subgraph) in the input graph, and extracted by Graph-Based Induction (GBI). We conducted four kinds of experiments using only the time-series data of blood inspection and urinalysis. In the first and second experiments, the stages of fibrosis were used as classes and a decision tree was constructed for discriminating patients with F4 (cirrhosis) from patients with the other stages. In the third experiment, the types of hepatitis (B and C) were used as classes, and in the fourth experiment the effectiveness of interferon therapy was used as the class label. The preliminary results of experiments, both constructed decision trees and their predictive accuracies, are reported in this paper.
منابع مشابه
Extracting Diagnostic Knowledge from Hepatitis Dataset by Decision Tree Graph-Based Induction
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