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Titlebook: Discovery Science; Third International Setsuo Arikawa,Shinichi Morishita Conference proceedings 2000 Springer-Verlag Berlin Heidelberg 200

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https://doi.org/10.1007/978-3-030-02206-8We also introduce a computationally efficient technique based on ordered-attributes. It reduces search space significantly and finds valid and general rules for single nodes in the networks. Empirical results are shown.
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https://doi.org/10.1007/978-3-319-03605-2nsider is the one described uniformly in terms of a distance over strings. Firstly, we introduce a notion of a recursively generable distance over strings, and define a k-neighbor closure of a language L as the collection of strings each of which is at most k distant from some string in L. Then we d
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https://doi.org/10.1007/978-3-319-03605-2nalyzing such a velocity distribution via a multivariate Maxwellian mixture model whose each component represents each of the multiple peaks. The parameters of the model are determined through the EM algorithm. For an auto judgment of preferable number of components of the mixture model, we introduc
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https://doi.org/10.1007/978-3-319-03605-2two steps. The first step is regression analysis. The second step is rule extraction from the regression formula obtained by the regression analysis. In this paper, we use nonparametric regression analysis as a regression analysis, since there are not sufficient data in knowledge discovery from fMRI
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Peter M. Winter,Leonard L. Firestones sometimes dificult to make complete experimental planning in which hypotheses guiding the experiments are established prior to executing the experiments. Even if the situation stands, experts in the field systematically organize their experimental processes. We propose Searching Experimental Schem
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Setsuo Arikawa,Shinichi MorishitaIncludes supplementary material:
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/e/image/281061.jpg
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Degrees of belief, random worlds, and maximum entropyinformation (such as “80have hepatitis”), and default information (such as “patients with pneumonia typically have fever”). The doctor may want to make decisions regarding a particular patient, using the KB in some principled way. To do this, it is often useful for the doctor to assign a numerical “
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