2009 |
18 | EE | David Martens,
Bart Baesens,
Tony Van Gestel:
Decompositional Rule Extraction from Support Vector Machines by Active Learning.
IEEE Trans. Knowl. Data Eng. 21(2): 178-191 (2009) |
2007 |
17 | EE | F. Hoffmann,
Bart Baesens,
Christophe Mues,
Tony Van Gestel,
Jan Vanthienen:
Inferring descriptive and approximate fuzzy rules for credit scoring using evolutionary algorithms.
European Journal of Operational Research 177(1): 540-555 (2007) |
16 | EE | David Martens,
Bart Baesens,
Tony Van Gestel,
Jan Vanthienen:
Comprehensible credit scoring models using rule extraction from support vector machines.
European Journal of Operational Research 183(3): 1466-1476 (2007) |
2006 |
15 | EE | Johan Huysmans,
David Martens,
Bart Baesens,
Jan Vanthienen,
Tony Van Gestel:
Country Corruption Analysis with Self Organizing Maps and Support Vector Machines.
WISI 2006: 103-114 |
14 | EE | Tony Van Gestel,
Bart Baesens,
Peter Van Dijcke,
Joao Garcia,
Johan A. K. Suykens,
Jan Vanthienen:
A process model to develop an internal rating system: Sovereign credit ratings.
Decision Support Systems 42(2): 1131-1151 (2006) |
13 | EE | Tony Van Gestel,
Bart Baesens,
Johan A. K. Suykens,
Dirk Van den Poel,
Dirk-Emma Baestaens,
Marleen Willekens:
Bayesian kernel based classification for financial distress detection.
European Journal of Operational Research 172(3): 979-1003 (2006) |
12 | EE | Bart Baesens,
Christophe Mues,
Tony Van Gestel,
Jan Vanthienen:
Special issue on intelligent information systems for financial engineering.
Expert Syst. Appl. 30(3): 413-414 (2006) |
11 | EE | Johan Huysmans,
Bart Baesens,
Jan Vanthienen,
Tony Van Gestel:
Failure prediction with self organizing maps.
Expert Syst. Appl. 30(3): 479-487 (2006) |
2004 |
10 | EE | Tony Van Gestel,
Johan A. K. Suykens,
Bart Baesens,
Stijn Viaene,
Jan Vanthienen,
Guido Dedene,
Bart De Moor,
Joos Vandewalle:
Benchmarking Least Squares Support Vector Machine Classifiers.
Machine Learning 54(1): 5-32 (2004) |
2003 |
9 | EE | Chuan Lu,
Tony Van Gestel,
Johan A. K. Suykens,
Sabine Van Huffel,
Dirk Timmerman,
Ignace Vergote:
Classification of Ovarian Tumors Using Bayesian Least Squares Support Vector Machines.
AIME 2003: 219-228 |
8 | EE | Chuan Lu,
Tony Van Gestel,
Johan A. K. Suykens,
Sabine Van Huffel,
Ignace Vergote,
Dirk Timmerman:
Preoperative prediction of malignancy of ovarian tumors using least squares support vector machines.
Artificial Intelligence in Medicine 28(3): 281-306 (2003) |
2002 |
7 | EE | Tony Van Gestel,
Johan A. K. Suykens,
Gert R. G. Lanckriet,
Annemie Lambrechts,
Bart De Moor,
Joos Vandewalle:
Bayesian Framework for Least-Squares Support Vector Machine Classifiers, Gaussian Processes, and Kernel Fisher Discriminant Analysis.
Neural Computation 14(5): 1115-1147 (2002) |
6 | | Tony Van Gestel,
Johan A. K. Suykens,
Gert R. G. Lanckriet,
Annemie Lambrechts,
Bart De Moor,
Joos Vandewalle:
Multiclass LS SVMs Moderated Outputs and Coding Decoding Schemes.
Neural Processing Letters 15(1): 45-58 (2002) |
2001 |
5 | EE | Tony Van Gestel,
Johan A. K. Suykens,
Bart De Moor,
Joos Vandewalle:
Automatic relevance determination for Least Squares Support Vector Machines classifiers.
ESANN 2001: 13-18 |
4 | EE | Tony Van Gestel,
Johan A. K. Suykens,
Jos De Brabanter,
Bart De Moor,
Joos Vandewalle:
Kernel Canonical Correlation Analysis and Least Squares Support Vector Machines.
ICANN 2001: 384-389 |
3 | | Stijn Viaene,
Bart Baesens,
Tony Van Gestel,
Johan A. K. Suykens,
Dirk Van den Poel,
Jan Vanthienen,
Bart De Moor,
Guido Dedene:
Knowledge discovery in a direct marketing case using least squares support vector machines.
Int. J. Intell. Syst. 16(9): 1023-1036 (2001) |
2000 |
2 | EE | Bart Baesens,
Stijn Viaene,
Tony Van Gestel,
Johan A. K. Suykens,
Guido Dedene,
Bart De Moor,
Jan Vanthienen:
An empirical assessment of kernel type performance for least squares support vector machine classifiers.
KES 2000: 313-316 |
1 | EE | Stijn Viaene,
Bart Baesens,
Tony Van Gestel,
Johan A. K. Suykens,
Dirk Van den Poel,
Jan Vanthienen,
Bart De Moor,
Guido Dedene:
Knowledge Discovery Using Least Squares Support Vector Machine Classifiers: A Direct Marketing Case.
PKDD 2000: 657-664 |