dr. A.J. (Ad) Feelders
A.J.Feelders@uu.nl
Gegenereerd op 2018-02-19 20:30:40


All publications
  2016 - Scholarly publications
Feelders, A.J. & Kolkman, Tijmen (2016). Exploiting Monotonicity Constraints to Reduce Label Noise: an Experimental Evaluation. 2016 International Joint Conference on Neural Networks (pp. 2148-2155) (8 p.). IEEE.
Masegosa, Andrés, Feelders, A.J. & van der Gaag, L.C. (2016). Learning from incomplete data in Bayesian networks with qualitative influences. International Journal of Approximate Reasoning, 69 (C), (pp. 18-34 ) (17 p.).
  2015 - Scholarly publications
Kreuzer, Robert, Hage, J. & Feelders, A.J. (2015). A Quantitative Comparison of Semantic Web Page Segmentation Approaches. Proceedings of ICWE 2015 (pp. 374-391). Springer.
Duivesteijn, Wouter, Feelders, Adrianus & Knobbe, Arno (04.02.2015). Exceptional Model Mining. Data Mining and Knowledge Discovery, (pp. 1-52) (52 p.).
Triepels, Ron, Feelders, A.J. & Daniels, Hennie (2015). Uncovering Document Fraud in Maritime Freight Transport Based on Probabilistic Classification. CISIM 2015 (pp. 282-293) (12 p.). Springer.
  2014 - Scholarly publications
Soons, Pieter & Feelders, Adrianus (2014). Exploiting monotonicity constraints for active learning in ordinal classification. In Mohammed Zaki, Zoran Obradovic, Pang Ning Tan, Arindam Banerjee, Chandrika Kamath & Srinivasan Parthasarathy (Eds.), Proceedings of the 2014 SIAM International Conference on Data Mining (pp. 659-667). SIAM.
Woudenberg, Steven, van der Gaag, Linda, Feelders, Adrianus & Elbers, Armin (2014). Real-time adaptive problem detection in poultry. Ecai 2014 - 21st european conference on artificial intelligence, 18-22 August 2014, Prague, Czech Republic (pp. 1217-1218) (2 p.). Amsterdam.
Woudenberg, Steven, van der Gaag, Linda, Feelders, Adrianus & Elbers, Armin (2014). Real-Time Adaptive Residual Calculation for Detecting Trend Deviations in Systems with Natural Variability. Advances in Intelligent Data Analysis XIII Springer.
  2013 - Scholarly publications
Mampaey, Michael, Nijssen, Siegfried, Feelders, Adrianus, Konijn, Rob & Knobbe, Arno (2013). Efficient algorithms for finding optimal binary features in numeric and nominal labeled data. Knowledge and Information Systems, 42 (2), (pp. 465-492).
  2012 - Scholarly publications
Barile, N. & Feelders, A.J. (2012). Active Learning with Monotonicity Constraints. SIAM International Conference on Data Mining (SDM 2012) (pp. 756-767) (12 p.).
Duivesteijn, W., Feelders, A.J. & Knobbe, A. (2012). Different Slopes for Different Folks: Mining for Exceptional Regression Models with Cook's Distance. ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Mampaey, M.J.R., Nijssen, S., Feelders, A.J. & Knobbe, A. (2012). Efficient Algorithms for Finding Richer Subgroup Descriptions in Numeric and Nominal Data. Proceedings of the IEEE International Conference on Data Mining (ICDM 2012)
van der Gaag, Linda, Bodlaender, Hans L. & Feelders, Ad (2012). Monotonicity in Bayesian Networks. CoRR, abs/1207.4160.
Roijers, D.M., Jeuring, J.T. & Feelders, A.J. (2012). Probability Estimation and a Competence Model for Rule-based e-Tutoring Systems. Learning Analytics and Knowledge (LAK 2012)
  2011 - Scholarly publications
Barile, N. & Feelders, A.J. (2011). Monotone Instance Ranking with MIRA. Proceedings of Discovery Science 2011 (pp. 31-45) (15 p.). Berlin: Springer.
Stegeman, L. & Feelders, A.J. (2011). On generating all optimal monotone classifications. 11th IEEE International Conference on Data Mining (pp. 685-694) (10 p.).
Pieters, B.F.I., van der Gaag, L.C. & Feelders, A.J. (2011). When Learning Naive Bayesian Classifiers Preserves Monotonicity. Proceedings of ECSQARU 2011 (pp. 422-433) (12 p.). Springer.
  2010 - Scholarly publications
Feelders, A.J. (2010). Monotone Relabeling in Ordinal Classification. In B. Liu & G.I. Webb (Eds.), 2010 IEEE International Conference On Data Mining (pp. 803-808) (6 p.). IEEE Computer Society CPS.
Duivesteijn, W., Knobbe, A.J., Feelders, A.J. & van Leeuwen, M. (2010). Subgroup Discovery meets Bayesian networks – an Exceptional Model Mining approach. In G.I. Webb, B. Liu, C. Zhang, D. Gunopulos & X. Wu (Eds.), Proceedings of the 10th IEEE International Conference on Data Mining (ICDM'10) (pp. 158-167) (10 p.). IEEE.
  2009 - Scholarly publications
van der Gaag, L.C., Renooij, S., Feelders, A.J., de Groote, A.J., Eijkemans, M.J.C., Broekmans, F.J. & Fauser, B.C.J.M. (23.07.2009). Aligning Bayesian Network Classifiers with Medical Contexts. In P Perner (Eds.), Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition (pp. 787-801) (15 p.). Berlin/Heidelberg: Springer, MLDM 2009.
van de Kamp, R., Feelders, A.J. & Barile, N. (2009). Isotonic Classification Trees. In N. Adams (Eds.), Proceedings of IDA 2009 (pp. 405-416) (12 p.). Springer, ida09.
Barile, N. & Feelders, A.J. (2009). Nonparametric Ordinal Classification with Monotonicity Constraints. In A. Feelders & R. Potharst (Eds.), Workshop Proceedings of MoMo 2009 (pp. 47-63) (17 p.). pkdd09.
  2008 - Scholarly publications
de Knijf, J. & Feelders, A.J. (2008). An Experimental Comparison of Different Inclusion Relations in Frequent Tree Mining. Fundamenta Informaticae, 89 (1), (pp. 1-22) (22 p.). fund08.
Kamphuis, C., Mollenhorst, H., Feelders, A.J. & Hogeveen, H. (2008). Decision tree induction for detection of clinical mastitis using data from six Dutch dairy herds milking with an automatic milking system. In T.J.G.M. Lam (Eds.), Mastitis control: From science to practice (pp. 267-274) (8 p.). mast08.
Leman, D., Feelders, A.J. & Knobbe, A.J. (2008). Exceptional Model Mining. Proceedings of ECML PKDD, Part II (pp. 1-16) (16 p.). EMM.
Duivesteijn, W. & Feelders, A.J. (2008). Nearest Neighbour Classification with Monotonicity Constraints. In W. Daelemans (Eds.), Proceedings of ECML/PKDD 2008 (pp. 301-316) (16 p.). Springer, pkdd08a.
Barile, N. & Feelders, A.J. (2008). Nonparametric Monotone Classification with MOCA. In F. Giannotti (Eds.), Proceedings of the Eighth IEEE International Conference on Data Mining (ICDM 2008) (pp. 731-736) (6 p.). IEEE Computer Society, icdm08.
  2008 - Professional publications
Feelders, A.J. (2008). Credit Scoring. In T. Rudas (Eds.), Handbook of probability: theory and applications (pp. 343-362) (20 p.). SAGE, sage08.
  2007 - Scholarly publications
Feelders, A.J. (2007). A new parameter learning method for Bayesian networks with qualitative influences. In R. Parr & L.C. van der Gaag (Eds.), Proceedings of Uncertainty in Artificial Intelligence 2007 (UAI07) (pp. 117-124) (8 p.). AUAI Press, uai07.
de Knijf, J. & Feelders, A.J. (2007). Choosing the Right Patterns: An Experimental Comparison between Different Tree Inclusion Relations. In D. Malerba, A. Appice & M. Ceci (Eds.), Proceedings of the Sixth International Workshop on Multi-Relational Data Mining (pp. 10-21) (12 p.).
Feelders, A.J. & van Straalen, R. (2007). Parameter Learning for Bayesian Networks with Strict Qualitative Influences. In M.R. Berthold, J. Shawe-Taylor & N. Lavrac (Eds.), Advances in Intelligent Data Analysis VII (pp. 48-58) (11 p.). Springer, ida07.
  2006 - Scholarly publications
Feelders, A.J. & Ivanovs, J. (2006). Discriminative Scoring of Bayesian Network Classifiers: a Comparative Study. In M. Studen'y & J. Vomlel (Eds.), Proceedings of the third European workshop on probabilistic graphical models (PGM'06) (pp. 75-82) (8 p.). pgm06.
Feelders, A.J. & van der Gaag, L.C. (2006). Learning Bayesian network parameters under order constraints. International Journal of Approximate Reasoning, 42, (pp. 37-53) (17 p.).
Velikova, M., Daniels, H & Feelders, A.J. (2006). Mixtures of Monotone Networks for Prediction. International Journal of Computational Intelligence, 3, (pp. 204-214) (11 p.). velikova:ijci.
Velikova, M., Daniels, H & Feelders, A.J. (2006). Solving partially monotone problems with neural networks. In R. Damasevicius (Eds.), Transactions on Engineering, Computing, and Technology (pp. 82-87) (6 p.). velikova:iccs.
  2005 - Scholarly publications
Helsper, E.M., van der Gaag, L.C., Feelders, A.J., Loeffen, W.L.A., Geenen, P.L. & Elbers, A.R.W. (2005). Bringing order into Bayesian-network construction. Proceedings of the Third International Conference on Knowledge Capture (pp. 121-128) (8 p.). New York: ACM Press.
Egmont-Petersen, M., Feelders, A.J. & Baesens, B. (2005). Confidence intervals for probabilistic network classifiers. Computational Statistics and Data Analysis, 49 (4), (pp. 998-1019) (22 p.).
Siebes, A.P.J.M., Subianto, M. & Feelders, A.J. (2005). Instability of Classifiers on Categorical Data. In J. Han, B.W. Wah, V. Raghavan, X. Wu & R. Rastogi (Eds.), Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005) (pp. 769-772) (4 p.). IEEE Computer Society, icdm05.
Riggelsen, C. & Feelders, A.J. (2005). Learning Bayesian Network Models from Incomplete Data using Importance Sampling. In Z. Ghahramani & R. Cowell (Eds.), Proceedings of the 10th International Workshop on Artificial Intelligence and Statistics (pp. 301-308) (8 p.). Society for Artificial Intellligence and Statistics, Riggel04b.
Feelders, A.J. & van der Gaag, L.C. (2005). Learning Bayesian network parameters with prior knowledge about context-specific qualitative influences. In F. Bacchus & T. Jaakkola (Eds.), Proceedings of the Twenty-first Conference on Uncertainty in Artificial Intelligence, (pp. 193-200) (8 p.). Corvallis: AUAI Press.
de Knijf, J. & Feelders, A.J. (2005). Monotone Constraints in Frequent Tree mining. In M. van Otterlo, M. Poel & A. Nijholt (Eds.), BENELEARN:Proceedingd of the 14 th Annual Machine Learning Conference of Belgium and the Netherlands (pp. 13-20) (8 p.).
  2004 - Scholarly publications
Feelders, A.J. & van der Gaag, L.C. (2004). Learning Bayesian Network Parameters Under Order Constraints. In P. Lucas (Eds.), Proceedings of the second European workshop on probabilistic graphical models (PGM'04) (pp. 73-80) (8 p.). pgm04.
van der Gaag, L.C., Bodlaender, H.L. & Feelders, A.J. (2004). Monotonicity in Bayesian Networks. In M. Chickering & J. Halpern (Eds.), Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (pp. 569-576) (8 p.). AUAI Press, uai04.
  2003 - Scholarly publications
Feelders, A.J. & Pardoel, M. (2003). Pruning for Monotone Classification Trees. In M.R. Berthold, H.J. Lenz, E. Bradley, R. Kruse & C. Borgelt (Eds.), Advances in Intelligent Data Analysis V Berlijn: Springer, pagina 1-12.
Feelders, A.J. (2003). Statistical Concepts. In M. Berthold & D.J. Hand (Eds.), Intelligent Data Analysis: an introduction (2nd edition) Berlijn: Springer.
  2003 - Professional publications
Feelders, A.J. (2003). Reject inference: distinguishing ignorable and non-ignorable selection mechanisms. Credit Risk International, (pp. 10-14) (5 p.). December 2003/January 2004.
  2002 - Scholarly publications
Potharst, R. & Feelders, A.J. (2002). Classification Trees for Problems with Monotonicity Constraints. SIGKDD Explorations, 4 (1), (pp. 1-10) (10 p.).
Feelders, A.J. (2002). Clustering. In J. Meij (Eds.), Dealing with the data flood (pp. 629-634) (6 p.). Den Haag, the Netherlands: STT/Beweton.
Feelders, A.J. (2002). Data Mining in Economic Science. In J. Meij (Eds.), Dealing with the data flood (pp. 166-175) (10 p.). Den Haag, the Netherlands: STT/Beweton.
Feelders, A.J. (2002). Rule induction by bump hunting. In J. Meij (Eds.), Dealing with the data flood (pp. 697-700) (4 p.). Den Haag, the Netherlands: STT/Beweton.
  2001 - Scholarly publications
Feelders, A.J. & Daniels, H.A.M. (2001). A general model for automated business diagnosis. European Journal of Operational Research, 130 (3), (pp. 623-637) (15 p.).
Castelo Valdueza, R., Feelders, A.J. & Siebes, A.P.J.M. (2001). Mambo: Discovering Association Rules Based on Conditional Independencies. In F. Hoffmann, D.J. Hand, N. Adams, D. Fisher & G. Guimaraes (Eds.), Advances in Intelligent Data Analysis (pp. 289-298) (10 p.). Berlin, Heidelberg, New York: Springer.
Siebes, A.P.J.M. & Feelders, A.J. (2001). OFFER: Making the right offer at customer contact. In V. Hoste & G. de Pauw (Eds.), Proceedings of the eleventh Belgian-Dutch Conference on Machine Learning (pp. 55-60) (6 p.). Antwerpen, Belgium.
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Gegenereerd op 2018-02-19 20:30:40
Full name
dr. A.J. Feelders Contact details
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Room BBL-563
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The Netherlands


Phone number (direct) +31 30 253 3176
Phone number (department) +31 30 253 9251
Gegenereerd op 2018-02-19 20:30:40
Last updated 06.03.2012