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Version space learning

Known as: Candidate elimination, Version Space, Version spaces 
Version space learning is a logical approach to machine learning, specifically binary classification. Version space learning algorithms search a… 
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2008
2008
Bipolarity appears in information processing when positive and negative sides of what is specified are clearly distinct, but not… 
2006
2006
In this paper, we are interested in learning stratified hypotheses from examples and counter-examples associated with weights… 
Review
2006
Review
2006
This paper surveys various areas in information engineering where an explicit handling of positive and negative sides of… 
2004
2004
In principle, the version space approach can be applied to any induction problem. However, in some cases the representation… 
2003
2003
In this paper we propose a lattice-based approach intended for extracting semantics from datacubes: borders of version spaces for… 
2002
2002
Version space is used in inductive concept learning to represent the hypothesis space where the goal concept is expressed as a… 
2000
2000
This paper presents an investigation of the numerical computations of nonweak/strong solutions of linear and nonlinear hyperbolic… 
1997
1997
Change management is a core problem of software development. Management of changes means managing the process of change as well… 
1983
1983
We approach concept learning as a heuristic search through a space of concepts for a concept that satisfies the learning task at…