Implementing an Integrated Time-Series Data Mining Environment Based on Temporal Pattern Extraction Methods: A Case Study of an Interferon Therapy Risk Mining for Chronic Hepatitis

Abstract

-In this paper, we present the implementation of an integrated time-series data mining environment. Time-series data mining is one of key issues to get useful knowledge from data bases. To execute time-series data mining smoothly, we have designed an environment which integrates time-series pattern extraction methods, rule induction methods and rule evaluation methods with active human-system interaction. After implementing this environment, we have done a case study to mine time-series rules from blood/urine biochemical test data base on chronic hepatitis patients. Then a physician has evaluated and refined his hypothesis on this environment. We discuss the availability of how much support to mine interesting knowledge for an expert.

Evaluating Learning Costs to Predict Human Interests with Rule Evaluation Models based on Objective Indices

“…In this section, we first present the results of an empirical evaluations with the dataset obtained from the result of a meningitis data mining [1], that of two times of hepatitis data mining [2], [3]. Based on the experimental results, we discuss the followings: accuracy of rule evaluation models, minimum training subsets of the learning algorithms, and contents of the learned rule evaluation models.…”