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A. J. Feelders: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. A. J. Feelders
    Data mining and related techniques. [Citation Graph (0, 0)][DBLP]
    EUROSIM, 1996, pp:521-527 [Conf]
  2. Arno Siebes, Muhammad Subianto, A. J. Feelders
    Instability of Classifiers on Categorical Data. [Citation Graph (0, 0)][DBLP]
    ICDM, 2005, pp:769-772 [Conf]
  3. Robert Castelo, A. J. Feelders, Arno Siebes
    MAMBO: Discovering Association Rules Based on Conditional Independencies. [Citation Graph (0, 0)][DBLP]
    IDA, 2001, pp:289-298 [Conf]
  4. A. J. Feelders, Martijn Pardoel
    Pruning for Monotone Classification Trees. [Citation Graph (0, 0)][DBLP]
    IDA, 2003, pp:1-12 [Conf]
  5. Eveline M. Helsper, Linda C. van der Gaag, A. J. Feelders, Willie Loeffen, Petra Geenen, Armin Elbers
    Bringing order into bayesian-network construction. [Citation Graph (0, 0)][DBLP]
    K-CAP, 2005, pp:121-128 [Conf]
  6. A. J. Feelders
    Learning from Biased Data Using Mixture Models. [Citation Graph (0, 0)][DBLP]
    KDD, 1996, pp:102-107 [Conf]
  7. A. J. Feelders, Soong Chang, Geoffrey J. McLachlan
    Mining in the Presence of Selectivity Bias and its Application to Reject Inference. [Citation Graph (0, 0)][DBLP]
    KDD, 1998, pp:199-203 [Conf]
  8. A. J. Feelders, A. J. F. le Loux, J. W. van't Zand
    Data Mining for Loan Evaluation at ABN AMRO: A Case Study. [Citation Graph (0, 0)][DBLP]
    KDD, 1995, pp:106-111 [Conf]
  9. A. J. Feelders
    Prior Knowledge in Economic Applications of Data Mining. [Citation Graph (0, 0)][DBLP]
    PKDD, 2000, pp:395-400 [Conf]
  10. A. J. Feelders
    Handling Missing Data in Trees: Surrogate Splits or Statistical Imputation. [Citation Graph (0, 0)][DBLP]
    PKDD, 1999, pp:329-334 [Conf]
  11. Jack P. C. Kleijnen, A. J. Feelders, Russell C. H. Cheng
    Bootstrapping and Validation of Metamodels in Simulation. [Citation Graph (0, 0)][DBLP]
    Winter Simulation Conference, 1998, pp:701-705 [Conf]
  12. A. J. Feelders, Linda C. van der Gaag
    Learning Bayesian network parameters under order constraints. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 2006, v:42, n:1-2, pp:37-53 [Journal]
  13. Rob Potharst, A. J. Feelders
    Classification trees for problems with monotonicity constraints. [Citation Graph (0, 0)][DBLP]
    SIGKDD Explorations, 2002, v:4, n:1, pp:1-10 [Journal]
  14. Michael Egmont-Petersen, A. J. Feelders, Bart Baesens
    Confidence intervals for probabilistic network classifiers. [Citation Graph (0, 0)][DBLP]
    Computational Statistics & Data Analysis, 2005, v:49, n:4, pp:998-1019 [Journal]
  15. A. J. Feelders, Robert van Straalen
    Parameter Learning for Bayesian Networks with Strict Qualitative Influences. [Citation Graph (0, 0)][DBLP]
    IDA, 2007, pp:48-58 [Conf]
  16. A. J. Feelders, Linda C. van der Gaag
    Learning Bayesian Network Parameters with Prior Knowledge about Context-Specific Qualitative Influences. [Citation Graph (0, 0)][DBLP]
    UAI, 2005, pp:193-200 [Conf]
  17. Linda C. van der Gaag, Hans L. Bodlaender, A. J. Feelders
    Monotonicity in Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2004, pp:569-576 [Conf]

  18. Discriminative Scoring of Bayesian Network Classifiers: a Comparative Study. [Citation Graph (, )][DBLP]

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