On optimization of decision trees

被引：0

作者：

Chikalov, IV

Moshkov, MJ

Zelentsova, MS

机构：

[1] Russian Res Ctr, Intel Labs, Nizhnii Novgorod 603950, Russia

[2] Univ Silesia, Inst Comp Sci, PL-41200 Sosnowiec, Poland

[3] Novgorod State Univ, Fac Comp Math & Cybernet Nizhny, Nizhnii Novgorod 603950, Russia

来源：

TRANSACTIONS ON ROUGH SETS IV | 2005年 / 3700卷

关键词：

decision trees; complexity measures; optimization;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In the paper algorithms are considered which allow to consecutively optimize decision trees for decision tables with many-valued decisions relatively different complexity measures such as number of nodes, weighted depth, average weighted depth, etc. For decision tables over an arbitrary infinite restricted information system [5] these algorithms have (at least for the three mentioned measures) polynomial time complexity depending on the length of table description. For decision tables over one of such information systems experimental results of decision tree optimization are described.

引用

页码：18 / 36

页数：19

共 8 条

[1]

CHIKALOV IV, 2000, P 2 INT C ROUGH SETS, P107

[2]

CHIKALOV IV, 2000, P 8 INT C INF PROC M, V1, P376

[3]

CHLEBUS BS, 1998, LECT NOTES ARTIF INT, V1424, P537

[4]

Moshkov M., 2000, Fundamenta Informaticae, V41, P295

[5]

Moshkov MJ, 2004, FUND INFORM, V61, P87

[6]

MOSHKOV MJ, 1999, P 12 INT C PROBL T 2, P165

[7]

Pawlak Z., 1991, Rough sets: Theoretical aspects of reasoning about data, DOI DOI 10.1007/978-94-011-3534-4

[8]

Skowron A., 1992, Handbook of Applications and Advances of the Rough Sets Theory, DOI DOI 10.1007/978-94-015-7975-9_21

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