DocumentCode :
2363699
Title :
INNE: a structured learning algorithm for noisy examples
Author :
Liquiere, Michel ; Sallantin, Jean
Author_Institution :
CRIM, Montpellier, France
fYear :
1989
fDate :
23-25 Oct 1989
Firstpage :
70
Lastpage :
76
Abstract :
A technique for learning structural concepts from noisy examples is presented. Using the description language defined by J.F. Sowa (1984) provides a convenient way of expressing the knowledge and the properties used by the algorithm. This graph description makes it possible to better manage learning problems, define new methods, and present results in a familiar and practical way. A learning system INNE has been developed which is based on this kind of description language. The goal is to design a learning algorithm which allows the processing of a considerable amount of data in a reasonable time. This kind of learning engine has been successfully tested on a real problem in biology. Thus, an experimental basis and a validation of the method have been acquired
Keywords :
knowledge acquisition; knowledge based systems; learning systems; INNE; biology; description language; graph description; knowledge acquisition; learning engine; learning problems; noisy examples; structured learning algorithm; Algorithm design and analysis; Diseases; Learning systems; Logic; Machine learning; Machine learning algorithms; Mechanical factors; Medical treatment; Testing; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools for Artificial Intelligence, 1989. Architectures, Languages and Algorithms, IEEE International Workshop on
Conference_Location :
Fairfax, VA
Print_ISBN :
0-8186-1984-8
Type :
conf
DOI :
10.1109/TAI.1989.65304
Filename :
65304
Link To Document :
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