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Book Sections Year : 1994

Using constraints to building version spaces

Abstract

Our concern is building the set G of maximally general terms covering positive examples and rejecting negative examples in prepositional logic. Negative examples are represented as constraints on the search space. This representation allows for defining a partial order on the negative examples and on attributes too. It is shown that only minimal negative examples and minimal attributes are to be considered when building the set G. These results hold in case of a non-convergent data set. Constraints can be directly used for a polynomial characterization of G. They also allow for detecting erroneous examples in a data set.

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hal-03526141 , version 1 (14-01-2022)

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Michèle Sebag. Using constraints to building version spaces. Machine Learning: ECML-94, 784, Springer Berlin Heidelberg, pp.257-271, 1994, Lecture Notes in Computer Science, ⟨10.1007/3-540-57868-4_63⟩. ⟨hal-03526141⟩
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