Accurate methods for incomplete data analysis using the mixed trunsored model and the decision tree.

使用混合截断模型和决策树进行不完整数据分析的准确方法。

• 批准号: 17510127
• 负责人: HIROSE Hideo
• 金额: $ 1.25万
• 依托单位: Kyushu Institute of Technology
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2005
• 资助国家: 日本
• 起止时间: 2005 至 2007
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-17510127/
• 关键词: mixed trunsored model; decision tree; bump hunting; genetic algorithm; extreme-vale distribution; power law; classification; epidemiology; mixed trunsored model; decision tree; bump hunting; genetic algorithm; extreme-vale distribution; power

The objective of this project is to analyze the incomplete data cases where the data are consist of inhomogeneous data by estimating the model parameters and testing the hypotheses. To do this, first we tried to combine the data mining scheme with the incomplete data analysis methods.We have shown that the mixed trunsored model has applicability to many fields such as the medical area or the reliability fields. The fact that the paper of IEEE Transaction was awarded by Japanese IEEE Reliability Society shows that the research level is highly evaluated.Also, the bump hunting method, which is useful to classify the messy data, has been shown with algorithms, and the numerical examples in marketing have been illustrated. We have had many presentations in IEEE, IFORS, and HICSS etc.The combined method of the trunsored model and the decision tree model has been developed with a concrete example in electrical insulation applications.Thus, we have reached the goal we posed successfully.

该项目的目的是通过估计模型参数并测试假设来分析数据案例不完整的数据案例。为此，首先，我们尝试将数据挖掘方案与不完整的数据分析方法相结合。我们表明，混合的Trunsored模型对许多领域（例如医疗区域或可靠性领域）具有适用性。日本IEEE可靠性协会颁发了IEEE交易的论文，这一事实表明，研究水平得到了高度评​​估。此外，遇到狩猎方法（对于对杂物数据进行分类非常有用），已通过算法显示，并且在营销中的数值示例也得到了说明。我们在IEEE，IFORS和HICS等中进行了许多演示。Trunsored模型的组合方法，并且决策树模型是通过电气绝缘应用中的具体示例开发的。因此，我们已经成功实现了我们成功提出的目标。

项目成果

Advances in Computational Algorithms and Data Analysis

• DOI: 10.1007/978-1-4020-8919-0
• 发表时间: 2008-10
• 作者: S. Ao;B. Rieger;Su-shing Chen

新しい遺伝的アルゴリズムによるバンプ探索トレードオフ曲線の精度:シミュレーションデータ

使用新遗传算法的凹凸搜索权衡曲线的准确性：模拟数据

• 发表时间: 2008
• 作者: 朝長;行實;廣瀬
• 通讯作者: 廣瀬

カテゴリ別に行動規制したときの感染蔓延抑止効果についての一考察

分类限制行为对预防感染传播的效果研究

• 发表时间: 2007
• 作者: 豊坂;藤尾;廣瀬
• 通讯作者: 廣瀬

Assessment of the prediction accuracy in the bump hunting procedure

碰撞搜寻过程中预测精度的评估

• 发表时间: 2007
• 作者: H. Hirose;S. Ohi;T. Yukizane
• 通讯作者: T. Yukizane

決定木とワ才ブルべき乗則とを組み合わせた電力ケーブルの劣化要因分析とその余寿命推定

结合决策树和幂律分析电力电缆劣化因素并估计其剩余寿命

• 发表时间: 2007
• 作者: 鶴;廣瀬
• 通讯作者: 廣瀬