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
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