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Analysis of several decision fusion strategies for clustering validation. Strategy definition, experiments and validation.

A. Yera, O. Arbelaitz, J. Jodra, I. Gurrutxaga, J. Pérez, and J. Muguerza. Pattern Recognit. Lett., (2017)

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Said Ibaidi

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Consolidated Trees: Classifiers with Stable Explanation. A Model to Achieve the Desired Stability in Explanation.J. Pérez, J. Muguerza, O. Arbelaitz, I. Gurrutxaga, and J. Martín. ICAPR (1), volume 3686 of Lecture Notes in Computer Science, page 99-107. Springer, (2005)Diagnostic classification of Parkinson's disease based on non-motor manifestations and machine learning strategies.M. Martinez-Eguiluz, O. Arbelaitz, I. Gurrutxaga, J. Muguerza, I. Perona, A. Murueta-Goyena, M. Acera, R. Pino, B. Tijero, J. Gomez-Esteban and 1 other author(s). Neural Comput. Appl., 35 (8): 5603-5617 (March 2023)CT ;lt;DT>: Extending the application of the consolidation methodology even further.I. Ibarguren, J. Pérez, J. Muguerza, and I. Gurrutxaga. Expert Syst. J. Knowl. Eng., (2017)Consolidated Tree Construction Algorithm: Structurally Steady TreesJ. Pérez, J. Muguerza, O. Arbelaitz, and I. Gurrutxaga. ICEIS (2)'04, page 14-21. (2004)Consolidated Trees: An Analysis of Structural Convergence.J. Pérez, J. Muguerza, O. Arbelaitz, I. Gurrutxaga, and J. Martín. Selected Papers from AusDM, volume 3755 of Lecture Notes in Computer Science, Springer, (2006)Solving Poisson's equation using FFT in a GPU cluster.J. Jodrá, I. Gurrutxaga, J. Muguerza, and A. Yera. J. Parallel Distributed Comput., (2017)UnPART: PART without the 'partial' condition of it.I. Ibarguren, J. Pérez, J. Muguerza, I. Gurrutxaga, and O. Arbelaitz. Inf. Sci., (2018)Applying Resampling Methods for Imbalanced Datasets to Not So Imbalanced Datasets.O. Arbelaitz, I. Gurrutxaga, J. Muguerza, and J. Pérez. CAEPIA, volume 8109 of Lecture Notes in Computer Science, page 111-120. Springer, (2013)C4.5 Consolidation Process: An Alternative to Intelligent Oversampling Methods in Class Imbalance Problems.I. Albisua, O. Arbelaitz, I. Gurrutxaga, J. Muguerza, and J. Pérez. CAEPIA, volume 7023 of Lecture Notes in Computer Science, page 74-83. Springer, (2011)Unsupervised anomaly detection system for Nidis-s based on payload and probabilistic suffix trees.I. Perona, O. Arbelaitz, I. Gurrutxaga, J. Martín, J. Muguerza, and J. Pérez. IADIS AC (1), page 11-18. IADIS Press, (2009)

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Analysis of several decision fusion strategies for clustering validation. Strategy definition, experiments and validation.

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Said Ibaidi

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Analysis of several decision fusion strategies for clustering validation. Strategy definition, experiments and validation.

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Said Ibaidi

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Analysis of several decision fusion strategies for clustering validation. Strategy definition, experiments and validation.