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JETAI
2010
56views more  JETAI 2010»
13 years 6 months ago
Warning: statistical benchmarking is addictive. Kicking the habit in machine learning
Algorithm performance evaluation is so entrenched in the Machine Learning community that one could call it an addiction. Like most addictions, it is harmful and very difficult to ...
Chris Drummond, Nathalie Japkowicz
ICML
1998
IEEE
13 years 11 months ago
The Problem with Noise and Small Disjuncts
Many systems that learn from examples express the learned concept as a disjunction. Those disjuncts that cover only a few examples are referred to as small disjuncts. The problem ...
Gary M. Weiss, Haym Hirsh
GPEM
2002
104views more  GPEM 2002»
13 years 7 months ago
Genetic Programming-based Construction of Features for Machine Learning and Knowledge Discovery Tasks
In this paper we use genetic programming for changing the representation of the input data for machine learners. In particular, the topic of interest here is feature construction i...
Krzysztof Krawiec
ICTAI
2007
IEEE
14 years 2 months ago
ExOpaque: A Framework to Explain Opaque Machine Learning Models Using Inductive Logic Programming
In this paper we developed an Inductive Logic Programming (ILP) based framework ExOpaque that is able to extract a set of Horn clauses from an arbitrary opaque machine learning mo...
Yunsong Guo, Bart Selman
CIKM
2005
Springer
14 years 1 months ago
Information retrieval and machine learning for probabilistic schema matching
Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas e.g. in the data exchange domain, or for distribute...
Henrik Nottelmann, Umberto Straccia