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PAKDD
1999
ACM
113views Data Mining» more  PAKDD 1999»
13 years 11 months ago
Characterization of Default Knowledge in Ripple Down Rules Method
Abstract. \Ripple Down Rules (RDR)" Method is one of the promising approaches to directly acquire and encode knowledge from human experts. It requires data to be supplied incr...
Takuya Wada, Tadashi Horiuchi, Hiroshi Motoda, Tak...
KDD
1995
ACM
130views Data Mining» more  KDD 1995»
13 years 11 months ago
Compression-Based Evaluation of Partial Determinations
Our work tackles the problem of finding partial determinations in databases and proposes a compressionbased measure to evaluate them. Partial determinations can be viewed as gener...
Bernhard Pfahringer, Stefan Kramer
IDA
2007
Springer
13 years 7 months ago
Anomaly detection in data represented as graphs
An important area of data mining is anomaly detection, particularly for fraud. However, little work has been done in terms of detecting anomalies in data that is represented as a g...
William Eberle, Lawrence B. Holder
JMLR
2002
106views more  JMLR 2002»
13 years 7 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
IJAR
2010
130views more  IJAR 2010»
13 years 5 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki