\begin{thebibliography}{44}
\expandafter\ifx\csname natexlab\endcsname\relax\def\natexlab#1{#1}\fi
\expandafter\ifx\csname url\endcsname\relax
  \def\url#1{{\tt #1}}\fi

\bibitem[Agrawal et~al.(1996)Agrawal, Mannila, Srikant, Toivonen, and
  Verkamo]{Agrawaletal.1996}
Rakesh Agrawal, Heikki Mannila, Ramakrishnan Srikant, Hannu Toivonen, and
  A.~Inkeri Verkamo.
\newblock Fast discovery of association rules.
\newblock {\em Advances in Knowledge Discovery and Data Mining}, AAAI
  Press:\penalty0 307--328, 1996.

\bibitem[Cestnik(1990)]{ces:1990}
Bojan Cestnik.
\newblock Estimating probabilities: A crucial task in machine learning.
\newblock In {\em Proceedings of the Ninth European Conference on Artificial
  Intelligence}, pages 147--149, Pitman, 1990.

\bibitem[Clark and Boswell(1991)]{cla:bos:1991}
Peter Clark and Robin Boswell.
\newblock Rule induction with cn2: Some recent improvements.
\newblock In {\em Proceedings of the Fifth European Working Session on
  Learning}, pages 151--163, Springer, 1991.

\bibitem[Clark and Niblett(1989)]{cla:nib:1989}
Peter Clark and Tim Niblett.
\newblock The cn2 induction algorithm.
\newblock {\em Machine Learning}, 3\penalty0 (4):\penalty0 261--283, 1989.

\bibitem[Cohen(1995)]{cohen1995}
William~W. Cohen.
\newblock Fast effective rule induction.
\newblock In {\em Proceedings of the Twelfth International Conference on
  Machine Learning}, pages 115--123, Morgan Kaufmann, 1995.

\bibitem[Cohen and Singer(1999)]{cohen1999}
William~W. Cohen and Yoram Singer.
\newblock A simple, fast, and effective rule learner.
\newblock In {\em Proceedings of AAAI/IAAI}, pages 335--342, AAAI Press, 1999.

\bibitem[D\v{z}eroski et~al.(1993)D\v{z}eroski, Cestnik, and
  Petrovski]{Dzeroskietal.1993}
Sa\v{s}o D\v{z}eroski, Bojan Cestnik, and Igor Petrovski.
\newblock Using the m-estimate in rule induction.
\newblock {\em Journal of Computing and Information Technology}, 1\penalty0
  (1):\penalty0 37--46, 1993.

\bibitem[Ferri-Ram\'{\i}rez et~al.(2002)Ferri-Ram\'{\i}rez, Flach, and
  Hernandez-Orallo]{Ferrietal.2002}
Cesar Ferri-Ram\'{\i}rez, Peter~A. Flach, and Jose Hernandez-Orallo.
\newblock Learning decision trees using the area under the roc curve.
\newblock In {\em Proceedings of the Nineteenth International Conference on
  Machine Learning}, pages 139--146, Morgan Kaufmann, 2002.

\bibitem[Flach(2003)]{flach-icml03}
Peter~A. Flach.
\newblock The geometry of roc space: Understanding machine learning metrics
  through roc isometrics.
\newblock In {\em Proceedings of the Twentieth International Conference on
  Machine Learning}, pages 194--201, AAAI Press, 2003.

\bibitem[Flach and Savnik(1999)]{FlachandSavnik1999}
Peter~A. Flach and Iztok Savnik.
\newblock Database dependency discovery: A machine learning approach.
\newblock {\em AI Communications}, 12\penalty0 (3):\penalty0 139--160, 1999.

\bibitem[Freund and Shapire(1996)]{FreundandShapire1996}
Yoav Freund and Robert~E. Shapire.
\newblock Experiments with a new boosting algorithm.
\newblock In {\em Proceedings of the Thirteenth International Conference on
  Machine Learning}, pages 148--156, Morgan Kaufmann, 1996.

\bibitem[Friedman and Fisher(1999)]{FriedmanandFisher1999}
Jerome~H. Friedman and Nicholas~I. Fisher.
\newblock Bump hunting in high-dimensional data.
\newblock {\em Statistics and Computing}, 9:\penalty0 123--143, 1999.

\bibitem[F\"{u}rnkranz and Flach(2003)]{furnkranz-flach-icml03}
Johannes F\"{u}rnkranz and Peter~A. Flach.
\newblock An analysis of rule evaluation metrics.
\newblock In {\em Proceedings of the Twetieth International Conference on
  Machine Learning}, pages 202--209, AAAI Press, 2003.

\bibitem[Gamberger and Lavra\v{c}(2002)]{GambergerLavrac2002}
Dragan Gamberger and Nada Lavra\v{c}.
\newblock Expert guided subgroup discovery: Methodology and application.
\newblock {\em Journal of Artificial Intelligence Research}, 17:\penalty0
  501--527, 2002.

\bibitem[Gordon(1982)]{Gordon1982}
A.D. Gordon.
\newblock {\em Classification}.
\newblock Chapman and Hall, London, 1982.

\bibitem[Gowda and Diday(1992)]{GowdaandDiday1992}
K.~Chidananda Gowda and Edwin Diday.
\newblock Symbolic clustering using a new dissimilarity measure.
\newblock {\em IEEE Transactions on Systems, Man, and Cybernetics}, 22\penalty0
  (2):\penalty0 567--578, 1992.

\bibitem[Hand and Till(2001)]{HandandTill2001}
David~J. Hand and Robert~J. Till.
\newblock A simple generalisation of the area under the roc curve for multiple
  class classification problems.
\newblock {\em Machine Learning}, 45:\penalty0 171--186, 2001.

\bibitem[Hsu et~al.(1998)Hsu, Etzioni, and Soderland]{Hsu1998}
David Hsu, Oren Etzioni, and Stephen Soderland.
\newblock A redundant covering algorithm applied to text classification.
\newblock In {\em Proceedings of the AAAI Workshop on Learning from Text
  Categorization}, AAAI Press, 1998.

\bibitem[Jovanoski and Lavra\v{c}(2001)]{JovanoskiandLavrac2001}
Viktor Jovanoski and Nada Lavra\v{c}.
\newblock Classification rule learning with apriori-c.
\newblock In {\em Progress in Artificial Intelligence: Proceedings of the Tenth
  Portuguese Conference on Artificial Intelligence}, pages 44--51, Springer,
  2001.

\bibitem[Kav\v{s}ek et~al.(2003)Kav\v{s}ek, Lavra\v{c}, and
  Jovanoski]{Kavseketal.2003}
Branko Kav\v{s}ek, Nada Lavra\v{c}, and Viktor Jovanoski.
\newblock Apriori-sd: Adapting association rule learning to subgroup discovery.
\newblock In {\em Proceedings of the Fifth International Symposium on
  Intelligent Data Analysis}, pages 230--241, Springer, 2003.

\bibitem[Kl\"{o}sgen(1996)]{Klosgen1996}
Willi Kl\"{o}sgen.
\newblock Explora: A multipattern and multistrategy discovery assistant.
\newblock {\em Advances in Knowledge Discovery and Data Mining}, MIT
  Press:\penalty0 249--271, 1996.

\bibitem[Knobbe et~al.(2001)Knobbe, de~Haas, and Siebes]{Knobbeetal.2001}
Arno~J. Knobbe, Marc de~Haas, and Arno Siebes.
\newblock Propositionalisation and aggregates.
\newblock In {\em Proceedings of the Fifth European Conference on Principles
  and Practice of Knowledge Discovery in Databases}, pages 277--288, Springer,
  2001.

\bibitem[Knobbe et~al.(2002)Knobbe, Siebes, and Marseille]{Knobbeetal.2002}
Arno~J. Knobbe, Arno Siebes, and Bart Marseille.
\newblock Involving aggregate functions in multi-relational search.
\newblock In {\em Proceedings of the Sixth European Conference on Principles
  and Practice of Knowledge Discovery in Databases}, pages 287--298, Springer,
  2002.

\bibitem[Langley(1996)]{Langley1996}
Pat Langley.
\newblock {\em Elements of Machine Learning}.
\newblock Morgan Kaufmann, 1996.

\bibitem[Lavra\v{c} et~al.(2002)Lavra\v{c}, Flach, Kav\v{s}ek, and
  Todorovski]{Lavracetal.2002}
Nada Lavra\v{c}, Peter~A. Flach, Branko Kav\v{s}ek, and Ljup\v{c}o Todorovski.
\newblock Adapting classification rule induction to subgroup discovery.
\newblock In {\em Proceedings of the Second IEEE International Conference on
  Data Mining}, pages 266--273, IEEE Computer Society, 2002.

\bibitem[Lavra\v{c} et~al.(1999)Lavra\v{c}, Flach, and Zupan]{lav:fla:zup:1999}
Nada Lavra\v{c}, Peter~A. Flach, and Bla\v{z} Zupan.
\newblock Rule evaluation measures: A unifying view.
\newblock In {\em Proceedings of the Nineth International Workshop on Inductive
  Logic Programming}, pages 74--185, Springer, 1999.

\bibitem[Lavra\v{c} et~al.(2003)Lavra\v{c}, \v{Z}elezn\'{y}, and
  Flach]{Lavracetal.2002a}
Nada Lavra\v{c}, Filip \v{Z}elezn\'{y}, and Peter~A. Flach.
\newblock Rsd: Relational subgroup discovery through first-order feature
  construction.
\newblock In {\em Proceedings of the Twelfth International Conference on
  Inductive Logic Programming}, pages 149--165, Springer, 2003.

\bibitem[Lee et~al.(1998)Lee, Buchanan, and Aronis]{Leeetal.1998}
Yongwon Lee, Bruce~G. Buchanan, and John~M. Aronis.
\newblock Knowledge-based learning in exploratory science: Learning rules to
  predict rodent carcinogenicity.
\newblock {\em Machine Learning}, 30:\penalty0 217--240, 1998.

\bibitem[Ljubi\v{c} et~al.(2002)Ljubi\v{c}, Todorovski, Lavra\v{c}, and
  Bullas]{Ljubic:2002}
Peter Ljubi\v{c}, Ljup\v{c}o Todorovski, Nada Lavra\v{c}, and John~C. Bullas.
\newblock Time-series analysis of uk traffic accident data.
\newblock In {\em Proceedings of the Fifth International Multi-conference
  Information Society}, pages 131--134, 2002.

\bibitem[Michalski(1980)]{Michalski1980}
Ryszard~S. Michalski.
\newblock Pattern recognition as rule-guided inductive inference.
\newblock {\em IEEE Transactions on Pattern Analysis and Machine Intelligence},
  2\penalty0 (4):\penalty0 349--361, 1980.

\bibitem[Michalski et~al.(1986)Michalski, Mozeti\v{c}, Hong, and
  Lavra\v{c}]{Michalskietal.1986}
Ryszard~S. Michalski, Igor Mozeti\v{c}, Jiarong Hong, and N.~Lavra\v{c}.
\newblock The multi-purpose incremental learning system aq15 and its testing
  application on three medical domains.
\newblock In {\em Proceedings of the Fifth National Conference on Artificial
  Intelligence}, pages 1041--1045, Morgan Kaufmann, 1986.

\bibitem[Murphy and Aha(1994)]{mur:aha:1994}
Patrick~M. Murphy and David~W. Aha.
\newblock Uci repository of machine learning databases.
\newblock Available electronically at
  http://www.ics.uci.edu/~mlearn/MLRepository.html, 1994.

\bibitem[Provost and Fawcett(2001)]{ProvostandFawcett2001}
Foster~J. Provost and Tom Fawcett.
\newblock Robust classification for imprecise environments.
\newblock {\em Machine Learning}, 42\penalty0 (3):\penalty0 203--231, 2001.

\bibitem[Raedt and Blockeel(1997)]{DeRaedtandBlockeel1997}
Luc~De Raedt and Hendrik Blockeel.
\newblock Using logical decision trees for clustering.
\newblock In {\em Proceedings of the Seventh International Workshop on
  Inductive Logic Programming}, pages 133--140, Springer, 1997.

\bibitem[Raedt et~al.(2001)Raedt, Blockeel, Dehaspe, and Laer]{DeRaedt2001}
Luc~De Raedt, Hendrik Blockeel, Luc Dehaspe, and Wim~Van Laer.
\newblock Three companions for data mining in first order logic.
\newblock {\em Relational Data Mining}, Springer:\penalty0 106--139, 2001.

\bibitem[Raedt and Dehaspe(1997)]{DeRaedt1997}
Luc~De Raedt and Luc Dehaspe.
\newblock Clausal discovery.
\newblock {\em Machine Learning}, 26:\penalty0 99--146, 1997.

\bibitem[Rivest(1987)]{riv:1987}
Ronald~L. Rivest.
\newblock Learning decision lists.
\newblock {\em Machine Learning}, 2\penalty0 (3):\penalty0 229--246, 1987.

\bibitem[Schapire and Singer(1998)]{SchapireandSinger1998}
Robert~E. Schapire and Yoram Singer.
\newblock Improved boosting algorithms using confidence-rated predictions.
\newblock In {\em Proceedings of the Eleventh Conference on Computational
  Learning Theory}, pages 80--91, ACM Press, 1998.

\bibitem[Silberschatz and Tuzhilin(1995)]{Silberschatz95}
Avi Silberschatz and Alexander Tuzhilin.
\newblock On subjective measures of interestingness in knowledge discovery.
\newblock In {\em Proceedigns of the First International Conference on
  Knowledge Discovery and Data Mining}, pages 275--281, 1995.

\bibitem[Sokal and Sneath(1963)]{SokalandSneath1963}
R.R. Sokal and Peter~H.A. Sneath.
\newblock {\em Principles of Numerical Taxonomy}.
\newblock Freeman, San Francisco, 1963.

\bibitem[Todorovski et~al.(2000)Todorovski, Flach, and
  Lavra\v{c}]{tod:fla:lav:2000}
Ljup\v{c}o Todorovski, Peter~A. Flach, and Nada Lavra\v{c}.
\newblock Predictive performance of weighted relative accuracy.
\newblock In {\em Proceedings of the Fourth European Conference on Principles
  of Data Mining and Knowledge Discovery}, pages 255--264, Springer, 2000.

\bibitem[Witten and Frank(1999)]{wit:fra:1999}
Ian~H. Witten and Eibe Frank.
\newblock {\em Data Mining: Practical Machine Learning Tools and Techniques
  with Java Implementations}.
\newblock Morgan Kaufmann, 1999.

\bibitem[Wrobel(1997)]{Wrobel1997}
Stefan Wrobel.
\newblock An algorithm for multi-relational discovery of subgroups.
\newblock In {\em Proceedings of the First European Conference on Principles of
  Data Mining and Knowledge Discovery}, pages 78--87, Springer, 1997.

\bibitem[Wrobel(2001)]{Wrobel2001}
Stefan Wrobel.
\newblock Inductive logic programming for knowledge discovery in databases.
\newblock {\em Relational Data Mining}, Springer:\penalty0 74--101, 2001.

\end{thebibliography}
