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https://hdl.handle.net/2142/81903
Description
Title
Learning From a Monotonous, Ignorant Teacher
Author(s)
Mishra, Nina
Issue Date
1997
Doctoral Committee Chair(s)
Pitt, Leonard
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Artificial Intelligence
Language
eng
Abstract
"The third learning setting combines the first and second in that we both give our computer preclassified examples and allow it to pose membership queries. The unknown function f may now classify examples in one of three possible ways: ""+"", ""$-$"" or ""?"". We prove general results for when it is possible for a computer to learn to be ignorant in this three-valued setting (+, $-$, ?) that utilizes results from the two-valued (+, $-$) setting. The three-valued setting we consider differs from the standard three-valued setting in that the set of possible functions that f could be, together with the set of ""+"", ""$-$"" examples determine which examples can be classified ""?""."
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