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Classification of Interstate Conflict Outcomes Using a Bootstrapped CLS Algorithm

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dc.contributor.author Schrodt, Philip A.
dc.date.accessioned 2012-07-26T13:35:37Z
dc.date.available 2012-07-26T13:35:37Z
dc.date.issued 1987 en_US
dc.identifier.uri https://hdl.handle.net/10535/8257
dc.description.abstract "The CLS aglorithm is an inductive technique developed in artificial intelligence for generating classification trees from a set of data. These trees are similar to those used in expert systems; the advantage of the CLS algorithm is that the trees are being generated automatically rather than via human experts. This paper applies a bootstrapped version of CLS to the Butterworth Interstate Conflict data set. By generating a number of classification trees from randomly selected subsets of the complete data set, the variables which are the most effective in correctly classifying the cases can be identified and the degree of unpredictability in the data can be ascertained by computing the accuracy of the tree in classifying those cases not in the training set. In general, the technique works very well; the original set of 38 independent variables can be reduced to five or fewer with almost no loss of classification accuracy. Classification trees generated with these variable have 95%-100% accuracy when fitted into the entire set, and average 50%-60% accuracy when tested against validation samples in split-sample tests. Unlike existing statistical techniques, the knowledge representation structures inductively constructed by bootstrapped CLS are plausible models of human inductive theorizing since they fit within the known cognitive constraints of the brain." en_US
dc.language English en_US
dc.subject artificial intelligence en_US
dc.subject common pool resources en_US
dc.subject conflict--models en_US
dc.title Classification of Interstate Conflict Outcomes Using a Bootstrapped CLS Algorithm en_US
dc.type Conference Paper en_US
dc.type.published unpublished en_US
dc.type.methodology Case Study en_US
dc.subject.sector Theory en_US
dc.identifier.citationconference Meeting of the Intenational Studies Association en_US
dc.identifier.citationconfdates April en_US
dc.identifier.citationconfloc Washington, DC en_US


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