DECISION-TREE MODELING OF PROBABILITY-DISTRIBUTIONS

被引：0
作者：
JIROUSEK, R
机构：
来源：
INTERNATIONAL JOURNAL OF GENERAL SYSTEMS | 1994年 / 22卷 / 02期
关键词：
UNCERTAINTY PROCESSING; GRAPH MODELING; EXPLANATION;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Explanatory modules of probabilistic expert systems have to transform knowledge coded in the form of probability distributions into another form better adapted to human comprehension. For this purpose, decision trees are proposed. Their power to represent dependence structures of distributions is compared with that of graphical (decomposable) models.
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收藏
页码：125 / 137
页数：13
相关论文
共 19 条
  • [1] CESTNIK J, 1991, P EWSL91 PORTO
  • [2] CIAMPI A, 1991, INT SUMMER SCH COMPU
  • [3] GALLAGER RG, 1968, INFORMATION THEORY R
  • [4] HAJEK P, 1992, PROCESSING UNCERTAIN
  • [5] Jirousek R., 1990, Knowledge-Based Systems, V3, P7, DOI 10.1016/0950-7051(90)90032-D
  • [6] JIROUSEK R, 1992, JUL P INT C INF PROC, P497
  • [7] JIROUSEK R, 1988, 10TH T PRAG C INF TH, VB, P11
  • [8] JIROUSEK R, 1988, CYBERNETICS INFORMAT, P242
  • [9] JIROUSEK R, 1979, 8TH T PRAG C INF THE, VC, P189
  • [10] JIROUSEK R, 1992, 11TH T PRAG C INF TH, VB, P31
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