Titlebook: Rule Extraction from Support Vector Machines; Joachim Diederich (Honorary Professor) Book 2008 Springer-Verlag Berlin Heidelberg 2008 Supp

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David Martens,Johan Huysmans,Rudy Setiono,Jan Vanthienen,Bart Baesens adults. It is characterized by an impaired differentiation and aberrant clonal proliferation of immature myeloid precursors in the bone marrow that result in the accumulation of nonfunctional myeloblasts, impaired hematopoiesis, bone marrow failure, and peripheral blood cytopenias, thus increasing

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Glenn Fung,Sathyakama Sandilya,R. Bharat Raos, depending upon the underlying genetic lesion. Because the malignant cells in these tumors share many of the genetic (e.g., ongoing rearrangement of antigen receptor genes), and immunophenotypic (e.g., expression of progenitor markers such as CD34 and terminal deoxynucleotidyl transferase) propert

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Rule Extraction for Transfer LearningThis chapter discusses transfer learning, which is one practical application of rule extraction. In transfer learning, information from one learning experience is applied to speed up learning in a related task. The chapter describes several techniques for transfer learning in SVM-basedreinforcement learning, and shows results from a case study.

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Joachim Diederich (Honorary Professor)Introduces a number of different approaches to extracting rules from support vector machines developed by key researchers in the field.Successful applications are outlined and future research opportun

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Ground Beetles (Coleoptera: Carabidae): Their Potential as Bio-agents in Agroecosystems allowed productivity to increase, but not without consequences on the sustainability of the agroecosystem. In this chapter, we provided a brief account of the distribution and diversity by two case studies, prey record and biosafety of synthetic insecticides against carabids or ground beetles.