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KDD
1999
ACM
152views Data Mining» more  KDD 1999»
15 years 2 months ago
Applying General Bayesian Techniques to Improve TAN Induction
Tree Augmented Naive Bayes (TAN) has shown to be competitive with state-of-the-art machine learning algorithms [3]. However, the TAN induction algorithm that appears in [3] can be...
Jesús Cerquides
ECML
2007
Springer
15 years 1 months ago
Modeling Highway Traffic Volumes
Most traffic management and optimization tasks, such as accident detection or optimal vehicle routing, require an ability to adequately model, reason about and predict irregular an...
Tomás Singliar, Milos Hauskrecht
ESEM
2007
ACM
15 years 1 months ago
Comparison of Outlier Detection Methods in Fault-proneness Models
In this paper, we experimentally evaluated the effect of outlier detection methods to improve the prediction performance of fault-proneness models. Detected outliers were removed ...
Shinsuke Matsumoto, Yasutaka Kamei, Akito Monden, ...
KDD
1995
ACM
248views Data Mining» more  KDD 1995»
15 years 1 months ago
Data Mining for Loan Evaluation at ABN AMRO: A Case Study
Wedescribe a case study in data miningfor personal loan evaluation, performed at the ABNAMRObank in the Netherlands. Historical data of clients and their pay-backbehaviourare used...
A. J. Feelders, A. J. F. le Loux, J. W. van't Zand
ACIIDS
2010
IEEE
171views Database» more  ACIIDS 2010»
15 years 11 days ago
Evolving Concurrent Petri Net Models of Epistasis
Abstract. A genetic algorithm is used to learn a non-deterministic Petri netbased model of non-linear gene interactions, or statistical epistasis. Petri nets are computational mode...
Michael Mayo, Lorenzo Beretta