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Joint European Conference on Machine Learning and Knowledge Discovery in Databases

ECML PKDD 2012: Machine Learning and Knowledge Discovery in Databases pp 2–3Cite as

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Declarative Modeling for Machine Learning and Data Mining

Declarative Modeling for Machine Learning and Data Mining

  • Luc De Raedt20 
  • Conference paper
  • 4472 Accesses

  • 2 Citations

Part of the Lecture Notes in Computer Science book series (LNAI,volume 7523)

Abstract

Despite the popularity of machine learning and data mining today, it remains challenging to develop applications and software that incorporates machine learning or data mining techniques. This is because machine learning and data mining have focussed on developing high-performance algorithms for solving particular tasks rather than on developing general principles and techniques. I propose to alleviate these problems by applying the constraint programming methodology to machine learning and data mining and to specify machine learning and data mining problems as constraint satisfaction and optimization problems. What is essential is that the user be provided with a way to declaratively specify what the machine learning or data mining problem is rather than having to outline how that solution needs to be computed. This corresponds to a model + solver-based approach to machine learning and data mining, in which the user specifies the problem in a high level modeling language and the system automatically transforms such models into a format that can be used by a solver to efficiently generate a solution. This should be much easier for the user than having to implement or adapt an algorithm that computes a particular solution to a specific problem. Throughout the talk, I shall use illustrations from our work on constraint programming for itemset mining and probabilistic programming.

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Authors and Affiliations

  1. University of Leuven, Belgium

    Luc De Raedt

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  1. Luc De Raedt
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Editor information

Editors and Affiliations

  1. Intelligent Systems Laboratory, University of Bristol, Merchant Venturers Building, Woodland Road, BS8 1UB, Bristol, UK

    Peter A. Flach, Tijl De Bie & Nello Cristianini,  & 

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

De Raedt, L. (2012). Declarative Modeling for Machine Learning and Data Mining. In: Flach, P.A., De Bie, T., Cristianini, N. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2012. Lecture Notes in Computer Science(), vol 7523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33460-3_2

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  • DOI: https://doi.org/10.1007/978-3-642-33460-3_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33459-7

  • Online ISBN: 978-3-642-33460-3

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