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Automatically evolving rule induction algorithms
 Proc. of the 17th European Conf. on Machine Learning
"... Abstract. Research in the rule induction algorithm field produced many algorithms in the last 30 years. However, these algorithms are usually obtained from a few basic rule induction algorithms that have been often changed to produce better ones. Having these basic algorithms and their components in ..."
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Cited by 11 (4 self)
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Abstract. Research in the rule induction algorithm field produced many algorithms in the last 30 years. However, these algorithms are usually obtained from a few basic rule induction algorithms that have been often changed to produce better ones. Having these basic algorithms and their components
The BBG Rule Induction Algorithm
 In C. Rowles, H. Liu, & N. Foo (Eds
, 1993
"... We present an algorithm (BBG) for inductive learning from examples that outputs a rule list. BBG uses a combination of greedy and branchandbound techniques, and naturally handles noisy or stochastic learning situations. We also present the results of an empirical study comparing BBG with Quinl ..."
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Cited by 7 (2 self)
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We present an algorithm (BBG) for inductive learning from examples that outputs a rule list. BBG uses a combination of greedy and branchandbound techniques, and naturally handles noisy or stochastic learning situations. We also present the results of an empirical study comparing BBG
An Extended Genetic Rule Induction Algorithm
, 2000
"... This paper describes an extension of a GAbased, separateandconquer propositional rule induction algorithm called SIA [24]. While the original algorithm is computationally attractive and is also able to handle both nominal and continuous attributes efficiently, our algorithm further improves it by ..."
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Cited by 25 (0 self)
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This paper describes an extension of a GAbased, separateandconquer propositional rule induction algorithm called SIA [24]. While the original algorithm is computationally attractive and is also able to handle both nominal and continuous attributes efficiently, our algorithm further improves
A Fuzzy BeamSearch Rule Induction Algorithm
 Principles of Data Mining and Knowledge Discovery (Proc. 3rd European Conf.  PKDD99). Lecture Notes in Artificial Intelligence 1704
, 1999
"... . This paper proposes a fuzzy beam search rule induction algorithm for the classification task. The use of fuzzy logic and fuzzy sets not only provides us with a powerful, flexible approach to cope with uncertainty, but also allows us to express the discovered rules in a representation more intuitiv ..."
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Cited by 3 (1 self)
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. This paper proposes a fuzzy beam search rule induction algorithm for the classification task. The use of fuzzy logic and fuzzy sets not only provides us with a powerful, flexible approach to cope with uncertainty, but also allows us to express the discovered rules in a representation more
Creating Rule Ensembles From AutomaticallyEvolved Rule Induction Algorithms
"... Abstract Ensembles are a set of classification models that, when combined, produce better predictions than when used by themselves. This chapter proposes a new evolutionary algorithmbased method for creating an ensemble of rule sets consisting of two stages. First, an evolutionary algorithm (more p ..."
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precisely, a genetic programming algorithm) is used to automatically create complete rule induction algorithms. Secondly, the automaticallyevolved rule induction algorithms are used to produce rule sets that are then combined into an ensemble. Concerning this second stage, we investigate the effectiveness
Discovering New Rule Induction Algorithms with Grammarbased Genetic Programming
"... Summary. Rule induction is a data mining technique used to extract classification rules of the form IF (conditions) THEN (predicted class) from data. The majority of the rule induction algorithms found in the literature follow the sequential covering strategy, which essentially induces one rule at a ..."
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Cited by 1 (1 self)
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Summary. Rule induction is a data mining technique used to extract classification rules of the form IF (conditions) THEN (predicted class) from data. The majority of the rule induction algorithms found in the literature follow the sequential covering strategy, which essentially induces one rule
Automatically Evolving Rule Induction Algorithms Tailored to the Prediction of Postsynaptic Activity in Proteins
"... It is wellknown that no classification algorithm is the best in all application domains. The conventional approach for coping with this problem consists of trying to select the best classification algorithm for the target application domain. We propose a refreshing departure from this ∗Correspondin ..."
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this ∗Corresponding author 1 approach, consisting of automatically creating a rule induction algorithm tailored to the target application domain. This work proposes a grammarbased genetic programming (GGP) system to perform “algorithm construction”. The GGP is used to build a complete rule induction algorithm
The Design and Evaluation of a Rule Induction Algorithm
, 1993
"... We present an algorithm for inductive learning from examples that outputs an ordered list of ifthen rules as its hypothesis. The algorithm uses a combination of greedy and branchandbound techniques, and naturally handles noisy or stochastic learning situations. We also present the results of an e ..."
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Cited by 2 (2 self)
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We present an algorithm for inductive learning from examples that outputs an ordered list of ifthen rules as its hypothesis. The algorithm uses a combination of greedy and branchandbound techniques, and naturally handles noisy or stochastic learning situations. We also present the results
RULES6: A Simple Rule Induction Algorithm for Supporting Decision Making
"... Abstract – RULES3 Plus is a member of the RULES family of simple inductive learning algorithms with successful engineering applications. However, it requires modification in order to be a practical tool for problems involving large data sets. In particular, efficient mechanisms for handling continu ..."
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Cited by 2 (0 self)
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Abstract – RULES3 Plus is a member of the RULES family of simple inductive learning algorithms with successful engineering applications. However, it requires modification in order to be a practical tool for problems involving large data sets. In particular, efficient mechanisms for handling
A.A.: Towards a genetic programming algorithm for automatically evolving rule induction algorithms
 Proc. ECML/PKDD2004 Workshop on Advances in Inductive Learning. (2004) 93–108
"... Abstract. Rule induction is one of the techniques most used to extract knowledge from data, since the representation of knowledge as if/then rules is very intuitive and easily understandable by problemdomain experts. Existing rule induction algorithms have been manually designed. In this era of inc ..."
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Cited by 7 (0 self)
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Abstract. Rule induction is one of the techniques most used to extract knowledge from data, since the representation of knowledge as if/then rules is very intuitive and easily understandable by problemdomain experts. Existing rule induction algorithms have been manually designed. In this era
Results 1  10
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