ALFS - AN INDUCTIVE LEARNING ALGORITHM

被引：0

作者：

CIOS, KJ

MORAES, I

机构：

[1] University of Toledo, Toledo, Ohio

来源：

KYBERNETES | 1991年 / 20卷 / 03期

关键词：

ALGORITHMS; EXPERT SYSTEMS; KNOWLEDGE-BASED SYSTEMS; LEARNING;

D O I：

10.1108/eb005885

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

ALFS is an inductive learning algorithm that employs feature slection to learn concepts from examples. Features which best represent and differentiate a subset from other subsets in learning data are detected and used to produce rules. These rules form a knowledge base for an expert system. The performance of ALFS is illustrated using data sets from the domains of primary tumour and game playing.

引用

页码：18 / 29

页数：12

共 11 条

[1]

Bratko Ivan, 1987, INTERACTIONS ARTIFIC, P142

[2]

Breiman L, 2017, CLASSIFICATION REGRE, P368, DOI 10.1201/9781315139470

[3]

BUCHANAN BG, 1983, RULE BASED EXPERT SY

[4]

CARBONELL JG, 1983, MACHINE LEARNING ART

[5]

HOLLAND JH, 1986, INDUCTION PROCESS IN

[6] MATHEMATICAL METHODS OF FEATURE SELECTION IN PATTERN-RECOGNITION [J].

KITTLER, J .

INTERNATIONAL JOURNAL OF MAN-MACHINE STUDIES, 1975, 7 (05) :609-637

[7]

MICHALSKI R, 1986, AAAI 86, V2, P1041

[8]

MITCHELL T, 1986, MACH LEARN, V1, P56

[9]

PEARL J, 1985, TYPICAL USES HEURIST, pCH1

[10]

QUINLAN JR, 1986, 2ND P AUSTR C APPL E, P183

← 1 2 →