A. J. Feelders

Ad Feelders

	2011
35		Nicola Barile, Ad Feelders: Monotone Instance Ranking with mira. Discovery Science 2011: 31-45
34		Barbara F. I. Pieters, Linda C. van der Gaag, Ad Feelders: When Learning Naive Bayesian Classifiers Preserves Monotonicity. ECSQARU 2011: 422-433
33		Luite Stegeman, Ad Feelders: On Generating All Optimal Monotone Classifications. ICDM 2011: 685-694
	2010
32		Wouter Duivesteijn, Arno J. Knobbe, Ad Feelders, Matthijs van Leeuwen: Subgroup Discovery Meets Bayesian Networks -- An Exceptional Model Mining Approach. ICDM 2010: 158-167
31		Ad Feelders: Monotone Relabeling in Ordinal Classification. ICDM 2010: 803-808
	2009
30		Rémon van de Kamp, Ad Feelders, Nicola Barile: Isotonic Classification Trees. IDA 2009: 405-416
29		Linda C. van der Gaag, Silja Renooij, Ad Feelders, Arend de Groote, Marinus J. C. Eijkemans, Frank J. Broekmans, Bart C. J. M. Fauser: Aligning Bayesian Network Classifiers with Medical Contexts. MLDM 2009: 787-801
	2008
28		Wouter Duivesteijn, Ad Feelders: Nearest Neighbour Classification with Monotonicity Constraints. ECML/PKDD (1) 2008: 301-316
27		Dennis Leman, Ad Feelders, Arno J. Knobbe: Exceptional Model Mining. ECML/PKDD (2) 2008: 1-16
26		Nicola Barile, Ad Feelders: Nonparametric Monotone Classification with MOCA. ICDM 2008: 731-736
25		Jeroen De Knijf, Ad Feelders: An Experimental Comparison of Different Inclusion Relations in Frequent Tree Mining. Fundam. Inform. 89(1): 1-22 (2008)
	2007
24		A. J. Feelders, Robert van Straalen: Parameter Learning for Bayesian Networks with Strict Qualitative Influences. IDA 2007: 48-58
23		Ad Feelders: A new parameter Learning Method for Bayesian Networks with Qualitative Influences. UAI 2007: 117-124
	2006
22		A. J. Feelders, Jevgenijs Ivanovs: Discriminative Scoring of Bayesian Network Classifiers: a Comparative Study. Probabilistic Graphical Models 2006: 75-82
21		A. J. Feelders, Linda C. van der Gaag: Learning Bayesian network parameters under order constraints. Int. J. Approx. Reasoning 42(1-2): 37-53 (2006)
	2005
20		A. Fazel Famili, Joost N. Kok, José María Peña, Arno Siebes, A. J. Feelders: Advances in Intelligent Data Analysis VI, 6th International Symposium on Intelligent Data Analysis, IDA 2005, Madrid, Spain, September 8-10, 2005, Proceedings Springer 2005
19		Arno Siebes, Muhammad Subianto, A. J. Feelders: Instability of Classifiers on Categorical Data. ICDM 2005: 769-772
18		Eveline M. Helsper, Linda C. van der Gaag, A. J. Feelders, Willie Loeffen, Petra L. Geenen, Armin Elbers: Bringing order into bayesian-network construction. K-CAP 2005: 121-128
17		A. J. Feelders, Linda C. van der Gaag: Learning Bayesian Network Parameters with Prior Knowledge about Context-Specific Qualitative Influences. UAI 2005: 193-200
16		Michael Egmont-Petersen, A. J. Feelders, Bart Baesens: Confidence intervals for probabilistic network classifiers. Computational Statistics & Data Analysis 49(4): 998-1019 (2005)
	2004
15		Linda C. van der Gaag, Hans L. Bodlaender, A. J. Feelders: Monotonicity in Bayesian Networks. UAI 2004: 569-576
	2003
14		A. J. Feelders, Martijn Pardoel: Pruning for Monotone Classification Trees. IDA 2003: 1-12
	2002
13		Rob Potharst, A. J. Feelders: Classification trees for problems with monotonicity constraints. SIGKDD Explorations 4(1): 1-10 (2002)
	2001
12		Robert Castelo, A. J. Feelders, Arno Siebes: MAMBO: Discovering Association Rules Based on Conditional Independencies. IDA 2001: 289-298
11		A. J. Feelders, H. A. M. Daniels: A general model for automated business diagnosis. European Journal of Operational Research 130(3): 623-637 (2001)
	2000
10		A. J. Feelders: Prior Knowledge in Economic Applications of Data Mining. PKDD 2000: 395-400
9		A. J. Feelders, H. A. M. Daniels, Marcel Holsheimer: Methodological and practical aspects of data mining. Information & Management 37(5): 271-281 (2000)
8		A. J. Feelders: Credit scoring and reject inference with mixture models. Int. Syst. in Accounting, Finance and Management 9(1): 1-8 (2000)
	1999
7		A. J. Feelders: Handling Missing Data in Trees: Surrogate Splits or Statistical Imputation. PKDD 1999: 329-334
6		A. J. Feelders: Credit scoring and reject inference with mixture models. Int. Syst. in Accounting, Finance and Management 8(4): 271-279 (1999)
	1998
5		A. J. Feelders, Soong Chang, Geoffrey J. McLachlan: Mining in the Presence of Selectivity Bias and its Application to Reject Inference. KDD 1998: 199-203
4		Jack P. C. Kleijnen, A. J. Feelders, Russell C. H. Cheng: Bootstrapping and Validation of Metamodels in Simulation. Winter Simulation Conference 1998: 701-705
	1996
3		A. J. Feelders: Data mining and related techniques. EUROSIM 1996: 521-527
2		A. J. Feelders: Learning from Biased Data Using Mixture Models. KDD 1996: 102-107
	1995
1		A. J. Feelders, A. J. F. le Loux, J. W. van't Zand: Data Mining for Loan Evaluation at ABN AMRO: A Case Study. KDD 1995: 106-111

Coauthor Index

1	Bart Baesens	[16]
2	Nicola Barile	[26] [30] [35]
3	Hans L. Bodlaender	[15]
4	Frank J. Broekmans	[29]
5	Robert Castelo	[12]
6	Soong Chang	[5]
7	Russell C. H. Cheng	[4]
8	H. A. M. Daniels	[9] [11]
9	Wouter Duivesteijn	[28] [32]
10	Michael Egmont-Petersen	[16]
11	Marinus J. C. Eijkemans	[29]
12	Armin Elbers	[18]
13	Fazel Famili (A. Fazel Famili)	[20]
14	Bart C. J. M. Fauser	[29]
15	Linda C. van der Gaag	[15] [17] [18] [21] [29] [34]
16	Petra L. Geenen	[18]
17	Arend de Groote	[29]
18	Eveline M. Helsper	[18]
19	Marcel Holsheimer	[9]
20	Jevgenijs Ivanovs	[22]
21	Rémon van de Kamp	[30]
22	Jack P. C. Kleijnen	[4]
23	Jeroen De Knijf	[25]
24	Arno J. Knobbe	[27] [32]
25	Joost N. Kok	[20]
26	Matthijs van Leeuwen	[32]
27	Dennis Leman	[27]
28	Willie Loeffen	[18]
29	A. J. F. le Loux	[1]
30	Geoffrey J. McLachlan	[5]
31	Martijn Pardoel	[14]
32	José María Peña	[20]
33	Barbara F. I. Pieters	[34]
34	Rob Potharst	[13]
35	Silja Renooij	[29]
36	Arno Siebes	[12] [19] [20]
37	Luite Stegeman	[33]
38	Robert van Straalen	[24]
39	Muhammad Subianto	[19]
40	J. W. van't Zand	[1]

Colors in the list of coauthors

Last update Wed May 30 22:34:44 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page