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A user driven data mining process model and learning system

Ge, Esther, Nayak, Richi, & Xu, Yue (2008) A user driven data mining process model and learning system. In The 13th International Conference on Database Systems for Advanced Applications, 19-21 March 2008, New Delhi, India.

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Abstract

This paper deals with the problem of using the data mining models in a real-world situation where the user can not provide all the inputs with which the predictive model is built. A learning system framework, Query Based Learning System (QBLS), is developed for improving the performance of the predictive models in practice where not all inputs are available for querying to the system. The automatic feature selection algorithm called Query Based Feature Selection (QBFS) is developed for selecting features to obtain a balance between the relative minimum subset of features and the relative maximum classification accuracy. Performance of the QBLS system and the QBFS algorithm is successfully demonstrated with a real-world application

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2 citations in Scopus
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ID Code: 27221
Item Type: Conference Paper
Keywords: CRC for Construction Innovation, Program B : Sustainable Built Assets , Project 2005-003-B : Learning System for Life Prediction of Infrastructure
DOI: 10.1007/978-3-540-78568-2_7
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2008 Icon.Net Pty Ltd
Copyright Statement: The Participants of the CRC for Construction Innovation have delegated authority to the CEO of the CRC to give Participants permission to publish material created by the CRC for Construction Innovation. This delegation is contained in Clause 30 of the Agreement for the Establishment and Operation of the Cooperative Research Centre for Construction Innovation. The CEO of the CRC for Construction Innovation gives permission to the Queensland University of Technology to publish the papers/publications provided in the collection in QUT ePrints provided that the publications are published in full. Icon.Net Pty Ltd retains copyright to the publications. Any other usage is prohibited without the express permission of the CEO of the CRC. The CRC warrants that Icon.Net Pty Ltd holds copyright to all papers/reports/publications produced by the CRC for Construction Innovation.
Deposited On: 04 Sep 2009 12:22
Last Modified: 17 Jul 2014 14:23

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