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Using Genetic Programming for an Advanced Performance Assessment of Industrially Relevant Heterogeneous Catalysts

Materials and manufacturing processes, 2009-03, Vol.24 (3), p.282-292

2009

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Darwinian, Lamarckian, and Baldwinian (Co)Evolutionary Approaches for Feature Weighting in K-@@imeans@- Based Algorithms

IEEE transactions on evolutionary computation, 2008-10, Vol.12 (5), p.617-629

2008

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Darwinian, Lamarckian, and Baldwinian (Co)Evolutionary Approaches for Feature Weighting in [Formula Omitted]-means-Based Algorithms

IEEE transactions on evolutionary computation, 2008-10, Vol.12 (5), p.617

2008

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Comparison between two coevolutionary feature weighting algorithms in clustering

Pattern recognition, 2008-03, Vol.41 (3), p.983-994

2008

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MACLAW: A modular approach for clustering with local attribute weighting

Pattern recognition letters, 2006-08, Vol.27 (11), p.1299-1306

2006

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Darwinian, Lamarckian, and Baldwinian (Co)Evolutionary Approaches for Feature Weighting in K-means-Based Algorithms

IEEE transactions on evolutionary computation, 2008-10, Vol.12 (5), p.617-629

2008

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Genetic Algorithms for Feature Weighting: Evolution vs. Coevolution and Darwin vs. Lamarck

Lecture notes in computer science, 2005, p.682-691

2005

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A Coevolutionary Approach for Clustering with Feature Weighting Application to Image Analysis

Applications of Evolutionary Computing, 2005, p.254-263

2005

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Testing the CAX on a Real-World Problem and Other Benchmarks

Parallel Problem Solving from Nature – PPSN X, p.599-609

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Comparison of MACLAW with several attribute selection methods for classification in hyperspectral images

Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006, p.231-236

2006

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Interactive and iterative visual clustering

Information visualization, 2016-07, Vol.15 (3), p.181-197

2016

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Iterative Evolutionary Subspace Clustering

Neural Information Processing, p.424-431

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Visual and Dynamic Change Detection for Data Streams

Neural Information Processing, 2015, Vol.9491, p.402-410

2015

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Discovering New Orders of the Chemical Elements through Genetic Algorithms

Advances in Knowledge Discovery and Data Mining, p.849-857

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Exploitation of a parallel clustering algorithm on commodity hardware with P2P-MPI

The Journal of supercomputing, 2008, Vol.43 (1), p.21-41

2008

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Mining for Reengineering: An Application to Semantic Wikis Using Formal and Relational Concept Analysis

The Semanic Web: Research and Applications, p.421-435

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Using Genetic Programming for an Advanced Performance Assessment of Industrially Relevant Heterogeneous Catalysts

Darwinian, Lamarckian, and Baldwinian (Co)Evolutionary Approaches for Feature Weighting in K-@@imeans@- Based Algorithms

Darwinian, Lamarckian, and Baldwinian (Co)Evolutionary Approaches for Feature Weighting in [Formula Omitted]-means-Based Algorithms

Comparison between two coevolutionary feature weighting algorithms in clustering

MACLAW: A modular approach for clustering with local attribute weighting

Darwinian, Lamarckian, and Baldwinian (Co)Evolutionary Approaches for Feature Weighting in K-means-Based Algorithms

Genetic Algorithms for Feature Weighting: Evolution vs. Coevolution and Darwin vs. Lamarck

A Coevolutionary Approach for Clustering with Feature Weighting Application to Image Analysis

Testing the CAX on a Real-World Problem and Other Benchmarks

Comparison of MACLAW with several attribute selection methods for classification in hyperspectral images

Interactive and iterative visual clustering

Iterative Evolutionary Subspace Clustering

Visual and Dynamic Change Detection for Data Streams

Discovering New Orders of the Chemical Elements through Genetic Algorithms

Exploitation of a parallel clustering algorithm on commodity hardware with P2P-MPI

Mining for Reengineering: An Application to Semantic Wikis Using Formal and Relational Concept Analysis

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