期刊文献+

一种新的判别决策树的建树准则 被引量:2

Alternative Evaluation Criterion of Constructing Decision Tree of Discrimination
在线阅读 下载PDF
导出
摘要 讨论了一种新的判别决策树评价准则,在建立二分树的过程中,提出采用不可分辨度最大下降作为选择自变量的原则.这种新准则与经典的非纯度下降算法在概念上是近似的.如果适当定义非纯度下降算法中的权重,则这两个准则就是完全等价的.然而,新准则的计算更加简单,并且通过案例分析可知。 An alternative criterion of evaluating the built decision tree for discrimination is discussed in this paper. The maximal decrease in undistinguished degree is proposed as the principle to choice explanatory variable for building a binary tree. From the basic concept, this new criterion is approximately consistent with the classical method using decrease in impurity. Though these two criteria are equivalent if choosing appropriate weights for the classical algorithm of decrease in impurity. The research shows that the computation of new criterion is more simple. Moreover, the result from the case study shows that the new criterion is more interpretable.
作者 王惠文
出处 《北京航空航天大学学报》 EI CAS CSCD 北大核心 2000年第1期111-113,共3页 Journal of Beijing University of Aeronautics and Astronautics
基金 国家自然科学基金!资助项目(79970053) 航空科学基金!资助项目(96J51124)
关键词 判别分析 决策树 纯度 不可分辨度 discriminant analysis decision trees purity undistinguished degree
  • 相关文献

参考文献2

  • 1刘永才 张卫.布尔方法理论[M].上海:上海科学技术文献出版社,1993..
  • 2刘永才,布尔方法理论,1993年

同被引文献10

  • 1张焱,欧阳一鸣,王浩,汪曦东.数据挖掘在金融领域中的应用研究[J].计算机工程与应用,2004,40(18):208-211. 被引量:19
  • 2Bores E, Hammer P L. An implementation of logical analysis of data[J]. IEEE Transactions on Knowledge and Data Engineering, 2000, (12): Issue, 2.
  • 3Breiman L, Friedman J H, Olshen R A, Stone C J. Classification and Regression Trees[M]. Wadsworth: 1984.
  • 4Diday E. From data to knowledge: Probabilistic Objects for a Symbolic Data Analysis[M]. Paris: Discrete Mathematics and Theoretical Computer Science, 1995.
  • 5Belson W A. Matching and prediction on the principal of biological classification[J]. Applied Statistics, 1995, (8):65--75.
  • 6Gettle-Summa M. Factorial axis interpretation by symbolic objects[J]. Analyze des connaissances, apprentissage,raisonnement. LISECEREMADE, University Paris IX-Dauphine, 1992. 53--64.
  • 7Batagelj V, Bren M. Comparing resemblance measures[J]. Journal of Classification, 1995, (12): 73--90.
  • 8Godin R, Missaoui R. An incremental concept formation approach for learning from databases[J]. Theoretical Computer Science, 1994, (133) : 387--409.
  • 9Jiawei Han, Micheline Kambr. Data Mining Concepts and Techniques. Morgan Kaufmann Publishers,2000.
  • 10邓念武,徐晖.单因变量的偏最小二乘回归模型及其应用[J].武汉大学学报(工学版),2001,34(2):14-16. 被引量:54

引证文献2

二级引证文献17

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部