DocumentCode :
1463483
Title :
Complexity of the consistency problem for certain Post classes
Author :
Shmulevich, Ilya ; Gabbouj, Moncef ; Astola, Jaakko
Author_Institution :
Int. Center for Signal Process., Tampere Univ. of Technol., Finland
Volume :
31
Issue :
2
fYear :
2001
fDate :
4/1/2001 12:00:00 AM
Firstpage :
251
Lastpage :
253
Abstract :
The complexity of the consistency problem for several important classes of Boolean functions is analyzed. The classes of functions under investigation are those which are closed under function composition or superposition. Several of these so-called Post classes are considered within the context of machine learning with an application to breast cancer diagnosis. The considered Post classes furnish a user-selectable measure of reliability. It is shown that for realistic situations which may arise in practice, the consistency problem for these classes of functions is polynomial-time solvable
Keywords :
Boolean functions; computational complexity; learning (artificial intelligence); Boolean functions; Post class; Post classes; complexity; computational complexity; computational learning theory; consistency problem; function composition; monotone Boolean function; polynomial-time solvable; superposition; Algebra; Boolean functions; Breast cancer; Control system synthesis; Machine learning; Manufacturing processes; Medical diagnosis; Polynomials; Signal analysis; Signal processing algorithms;
fLanguage :
English
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
1083-4419
Type :
jour
DOI :
10.1109/3477.915348
Filename :
915348
Link To Document :
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