G3P-MI: A genetic programming algorithm for multiple instance learning

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@Article{Zafra20104496,

• author = "Amelia Zafra and Sebastian Ventura",
• title = "{G3P-MI:} A genetic programming algorithm for multiple instance learning",
• journal = "Information Sciences",
• volume = "180",
• number = "23",
• pages = "4496--4513",
• year = "2010",
• ISSN = "0020-0255",
• DOI = "doi:10.1016/j.ins.2010.07.031",
• URL = "http://www.sciencedirect.com/science/article/B6V0C-50S2RDP-1/2/4591b7540f8c35538e14824742bb8343",
• keywords = "genetic algorithms, genetic programming, Multiple instance learning, Rule learning",
• abstract = "This paper introduces a new Grammar-Guided Genetic Programming algorithm for resolving multi-instance learning problems. This algorithm, called G3P-MI, is evaluated and compared to other multi-instance classification techniques in different application domains. Computational experiments show that the G3P-MI often obtains consistently better results than other algorithms in terms of accuracy, sensitivity and specificity. Moreover, it makes the knowledge discovery process clearer and more comprehensible, by expressing information in the form of IF-THEN rules. Our results confirm that evolutionary algorithms are very appropriate for dealing with multi-instance learning problems.",

}

Genetic Programming entries for Amelia Zafra Gomez Sebastian Ventura

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