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Auflistung nach Schlagwort "logistic regression"

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  • Konferenzbeitrag
    A Bayesian Update to Software Quality Modeling
    Härtel, Johannes; Lämmel, Ralf
    Software reengineering profits from quantitative definitions of software quality. Such definitions are often given in terms of software quality models. We show a Bayesian reformulation of an established software quality model (logistic regression model for defects), in particular, of a software defect model. We evaluate correspondence of the results, and show an acceptable computation overhead of the Bayesian model. We argue on why the Bayesian version may be an improvement, discussing its definition and the representation of results. We focus on modeling the quality of defect proneness. Methodological insights can be transferred to other qualities.
  • Konferenzbeitrag
    On Coresets for Logistic Regression
    (INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft, 2019) Munteanu, Alexander; Schwiegelshohn, Chris; Sohler, Christian; Woodruff, David P.
    Coresets are one of the central methods to facilitate the analysis of large data.We continue a recent line of research applying the theory of coresets to logistic regression. First, we show the negative result that no strongly sublinear sized coresets exist for logistic regression. To deal with intractable worst-case instances we introduce a complexity measure µ(X), which quantifies the hardness of compressing a data set for logistic regression. µ(X) has an intuitive statistical interpretation that may be of independent interest. For data sets with bounded µ(X)-complexity, we show that a novel sensitivity sampling scheme produces the first provably sublinear (1 ± ")-coreset.