Accuracy of the Solution in the Bump Hunting


行實, 廣瀬, 大井, 宮野

Takashi YUKIZANE, Hideo HIROSE, Shin-ya OHI, and Eiji MIYANO


情報処理学会MPS62BIO7合同研究発表会、pp.13-16 (平成18.12.21) 電気通信大学(調布)




Suppose that we are interested in searching for denser regions showing response 1 with many feature variables in a z-dimensional space, where each point is assigned response 1 or response 0 as its target value; such a region is called the bump or the hot-spot. In a series of the previous study, we have shown that the bump hunting using the decision tree is useful in the ease-of-use and the prediction capability view points, and have developed a new bump hunting method using probabilistic (GA) and statistical (extreme-value statistics) methods. However, the accuracy of the estimated maximum capture rate was assessed by using the simple bootstrap method without correction formula. We have not thought seriously of the bias and the variance to the predicted estimate; we are, however, now aware of that we should treat the value of the predicted estimate very carefully. Thus, we have proposed a new method to assess the prediction error in the bump hunting problem, where the test sample method and the bootstrap method are nicely combined.

Key Words

決定木,遺伝的アルゴリズム, 交差検証法,ブートストラップ法,ブートストラップ的テストサンプル法,バイアス

decision tree, genetic algorithm, cross-validation, bootstrap, bootstrapped test sample method, bias.



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