6 research outputs found

    Data Mining with Newton\u27s Method.

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    Capable and well-organized data mining algorithms are essential and fundamental to helpful, useful, and successful knowledge discovery in databases. We discuss several data mining algorithms including genetic algorithms (GAs). In addition, we propose a modified multivariate Newton\u27s method (NM) approach to data mining of technical data. Several strategies are employed to stabilize Newton\u27s method to pathological function behavior. NM is compared to GAs and to the simplex evolutionary operation algorithm (EVOP). We find that GAs, NM, and EVOP all perform efficiently for well-behaved global optimization functions with NM providing an exponential improvement in convergence rate. For local optimization problems, we find that GAs and EVOP do not provide the desired convergence rate, accuracy, or precision compared to NM for technical data. We find that GAs are favored for their simplicity while NM would be favored for its performance

    Private data base access schemes avoiding data distribution

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    Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (p. 71-72).by Yael Gertner.M.Eng

    Erzeugung Mehrfach Imputierter Synthetischer Datensätze: Theorie und Implementierung

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    The book describes different approaches to generating multiply imputed synthetic datasets to guarantee confidentiality. Each chapter is dedicated to one approach, first describing the general concept followed by a detailed application to a real dataset providing useful guidelines on how to implement the theory in practice.Die Arbeit beschreibt verschiedene Ansätze zur Erstellung mehrfach imputierter synthetischer Datensätze. Diese Datensätze können der interessierten Fachöffentlichkeit zur Verfügung gestellt werden, ohne den Datenschutz zu verletzen. Jedes Kapitel befasst sich mit einem eigenen Ansatz, wobei zunächst das allgemeine Konzept beschrieben wird. Anschließend bietet eine detailierte Anwendung auf einen realen Datensatz hilfreiche Richtlinien, wie sich die beschriebene Theorie in der Praxis anwenden läßt
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