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Accuracy-Based Learning Classifier Systems: Models, Analysis and Applications to Classification Tasks
TLDR
This paper investigates two models of accuracy-based learning classifier systems on different types of classification problems. Expand
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Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy, and Comparative Study
TLDR
The classification problem can be addressed by numerous techniques and algorithms which belong to different paradigms of machine learning. Expand
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Evolutionary rule-based systems for imbalanced data sets
TLDR
This paper investigates the capabilities of evolutionary on-line rule-based systems, also called learning classifier systems (LCSs), for extracting knowledge from imbalanced data. Expand
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XCS and GALE: A Comparative Study of Two Learning Classifier Systems on Data Mining
TLDR
This paper compares the learning performance, in terms of prediction accuracy, of two genetic-based learning systems, XCS and GALE, with six well-known learning algorithms, coming from instance based learning, decision tree induction, rule-learning, statistical modeling and support vector machines. Expand
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Bounding XCS's parameters for unbalanced datasets
TLDR
This paper analyzes the behavior of the XCS classifier system on imbalanced datasets. Expand
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Revisiting UCS: Description, Fitness Sharing, and Comparison with XCS
TLDR
This paper provides a deep insight into the learning mechanisms of UCS, a learning classifier system (LCS) derived from XCS that works under a supervised learning scheme. Expand
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Towards UCI+: A mindful repository design
TLDR
We analyse the type, complexity, and use of the most popular data repository in machine learning-the UCI repository-is examined. Expand
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Learning Classifier Systems: Looking Back and Glimpsing Ahead
TLDR
Learning Classifier Systems (LCSs) are robust machine learning techniques that can be applied to classification tasks [17, 6], large-scale data mining problems [80, 11]. Expand
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Domain of competence of XCS classifier system in complexity measurement space
TLDR
The XCS classifier system has recently shown a high degree of competence on a variety of data mining problems, but to what kind of problems XCS is well and poorly suited is seldom understood. Expand
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Genetic-based machine learning systems are competitive for pattern recognition
TLDR
This paper reviews the state of the art in GBML, selects some of the best representatives of different families, and compares the accuracy and the interpretability of their models. Expand
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