J
Jan Vanthienen
Researcher at Katholieke Universiteit Leuven
Publications - 299
Citations - 11665
Jan Vanthienen is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: Process mining & Decision table. The author has an hindex of 48, co-authored 291 publications receiving 10299 citations. Previous affiliations of Jan Vanthienen include The Catholic University of America.
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Book ChapterDOI
Process Mining Manifesto
Wil M. P. van der Aalst,Wil M. P. van der Aalst,A Arya Adriansyah,Ana Karla Alves de Medeiros,Franco Arcieri,Thomas Baier,Tobias Blickle,Jagadeesh Chandra Bose,Peter van den Brand,Ronald Brandtjen,Joos C. A. M. Buijs,Andrea Burattin,Josep Carmona,Malu Castellanos,Jan Claes,Jonathan Cook,Nicola Costantini,Francisco Curbera,Ernesto Damiani,Massimiliano de Leoni,Pavlos Delias,Boudewijn F. van Dongen,Marlon Dumas,Schahram Dustdar,Dirk Fahland,Diogo R. Ferreira,Walid Gaaloul,Frank van Geffen,Sukriti Goel,CW Christian Günther,Antonella Guzzo,Paul Harmon,Arthur H. M. ter Hofstede,Arthur H. M. ter Hofstede,John Hoogland,Jon Espen Ingvaldsen,Koki Kato,Rudolf Kuhn,Akhil Kumar,Marcello La Rosa,Fabrizio Maria Maggi,Donato Malerba,RS Ronny Mans,Alberto Manuel,Martin McCreesh,Paola Mello,Jan Mendling,Marco Montali,Hamid Reza Motahari-Nezhad,Michael zur Muehlen,Jorge Munoz-Gama,Luigi Pontieri,Joel Ribeiro,A Anne Rozinat,Hugo Seguel Pérez,Ricardo Seguel Pérez,Marcos Sepúlveda,Jim Sinur,Pnina Soffer,Minseok Song,Alessandro Sperduti,Giovanni Stilo,Casper Stoel,Keith D. Swenson,Maurizio Talamo,Wei Tan,Christopher Turner,Jan Vanthienen,George Varvaressos,Eric Verbeek,Marc Verdonk,Roberto Vigo,Jianmin Wang,Barbara Weber,Matthias Weidlich,Ton Weijters,Lijie Wen,Michael Westergaard,Moe Thandar Wynn +78 more
TL;DR: This manifesto hopes to serve as a guide for software developers, scientists, consultants, business managers, and end-users to increase the maturity of process mining as a new tool to improve the design, control, and support of operational business processes.
Journal ArticleDOI
Benchmarking state-of-the-art classification algorithms for credit scoring
TL;DR: It is found that both the LS-SVM and neural network classifiers yield a very good performance, but also simple classifiers such as logistic regression and linear discriminant analysis perform very well for credit scoring.
Journal ArticleDOI
Benchmarking Least Squares Support Vector Machine Classifiers
Tony Van Gestel,Johan A. K. Suykens,Bart Baesens,Stijn Viaene,Jan Vanthienen,Guido Dedene,Bart De Moor,Joos Vandewalle +7 more
TL;DR: Both the SVM and LS-SVM classifier with RBF kernel in combination with standard cross-validation procedures for hyperparameter selection achieve comparable test set performances, consistently very good when compared to a variety of methods described in the literature.
Journal ArticleDOI
Using Neural Network Rule Extraction and Decision Tables for Credit-Risk Evaluation
TL;DR: It is concluded that neural network rule extraction and decision tables are powerful management tools that allow us to build advanced and userfriendly decision-support systems for credit-risk evaluation.
Journal ArticleDOI
Classification With Ant Colony Optimization
TL;DR: This paper provides an overview of previous ant-based approaches to the classification task and compares them with state-of-the-art classification techniques, such as C4.5, RIPPER, and support vector machines in a benchmark study, and proposes a new AntMiner+.