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Combining Model-Based and Instance-Based Learning for First Order Regression Kurt Driessens Department of Computer Science, University of Waikato, Hamilton, New Zealand Saˇ
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Document Date: 2008-12-01 11:16:01


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City

Ljubljana / Hamilton / Bonn / Combining Model / /

Company

KBR / AAAI Press / New Zealand Sa / /

Country

Germany / /

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Facility

Carnegie Mellon University / University of Waikato / Joˇzef Stefan Institute / /

IndustryTerm

hybrid regression algorithm / rib algorithms / relational regression algorithms / rib regression algorithm / lazy learning algorithms / regression algorithms / Model-based algorithms / tg algorithm / incremental relational regression algorithm / model building algorithm / order regression algorithms / incremental first order regression algorithm / rib algorithm / relational regression algorithm / first order regression algorithms / regression algorithm / learning algorithms / model-based tg algorithm / incremental relational regression algorithms / /

OperatingSystem

Linux / /

Organization

Department of Knowledge Technologies / Joˇzef Stefan Institute / First Order Regression Kurt Driessens Department of Computer Science / University of Waikato / Robotics Institute / Carnegie Mellon University / /

Person

Kurt Driessens / Morgan Kaufmann / /

Position

author / /

PublishedMedium

Journal of the ACM / Machine Learning / Episodes / /

Technology

three existing relational regression algorithms / incremental relational regression algorithm / rib algorithm / RAM / rib regression algorithm / Model-based algorithms / Linux / relational regression algorithm / regression algorithm / RRL algorithm / order regression algorithm / incremental relational regression algorithms / RISE algorithm / Machine Learning / rib algorithms / Instancebased learning algorithms / tg algorithm / Trendi algorithm / order regression algorithms / model-based tg algorithm / existing regression algorithms / hybrid regression algorithm / lazy learning algorithms / regression algorithms / model building algorithm / /

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