Nada Lavrac
Nada Lavrac
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TitleCited byYear
Inductive Logic Programming.
N Lavrac, S Dzeroski
WLP, 146-160, 1994
The multi-purpose incremental learning system AQ15 and its testing application to three medical domains
RS Michalski, I Mozetic, J Hong, N Lavrac
Proc. AAAI 1986, 1,041-1,045, 1986
Intelligent data analysis
M Berthold, DJ Hand
Springer, 2003
Subgroup discovery with CN2-SD
N Lavrač, B Kavšek, P Flach, L Todorovski
Journal of Machine Learning Research 5 (Feb), 153-188, 2004
Rule evaluation measures: A unifying view
N Lavrač, P Flach, B Zupan
International Conference on Inductive Logic Programming, 174-185, 1999
Selected techniques for data mining in medicine
N Lavrač
Artificial intelligence in medicine 16 (1), 3-23, 1999
Supervised descriptive rule discovery: A unifying survey of contrast set, emerging pattern and subgroup mining
PK Novak, N Lavrač, GI Webb
Journal of Machine Learning Research 10 (Feb), 377-403, 2009
Propositionalization approaches to relational data mining
S Kramer, N Lavrač, P Flach
Relational data mining, 262-291, 2001
Informal identification of outliers in medical data
J Laurikkala, M Juhola, E Kentala, N Lavrac, S Miksch, B Kavsek
Fifth international workshop on intelligent data analysis in medicine and …, 2000
Learning nonrecursive definitions of relations with LINUS
N Lavrač, S Džeroski, M Grobelnik
European Working Session on Learning, 265-281, 1991
APRIORI-SD: Adapting association rule learning to subgroup discovery
B Kavšek, N Lavrač
Applied Artificial Intelligence 20 (7), 543-583, 2006
KARDIO: a study in deep and qualitative knowledge for expert systems
I Bratko, I Mozetič, N Lavrač
MIT Press, 1990
Expert-guided subgroup discovery: Methodology and application
D Gamberger, N Lavrac
Journal of Artificial Intelligence Research 17, 501-527, 2002
Foundations of rule learning
J Fürnkranz, D Gamberger, N Lavrač
Springer Science & Business Media, 2012
The AQ15 inductive learning system: an overview and experiments
R Michalski
Reports of Machine Learning and Inference Laboratory, 1986
Experiments with noise filtering in a medical domain
D Gamberger, N Lavrac, C Groselj
ICML, 143-151, 1999
Relational Data Mining
N Lavrac, S Dzeroski
Springer-Verlag New York, Inc., Secaucus, NJ, 2001
Stream-based active learning for sentiment analysis in the financial domain
J Smailović, M Grčar, N Lavrač, M Žnidaršič
Information sciences 285, 181-203, 2014
Comparative evaluation of approaches to propositionalization
MA Krogel, S Rawles, F Železný, PA Flach, N Lavrač, S Wrobel
International Conference on Inductive Logic Programming, 197-214, 2003
Propositionalization-based relational subgroup discovery with RSD
F Železný, N Lavrač
Machine Learning 62 (1-2), 33-63, 2006
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