Boosting random subspace method

DOI10.1016/J.NEUNET.2007.12.046zbMath1254.68202DBLPjournals/nn/Garcia-PedrajasO08OpenAlexW2058796521WikidataQ45964733 ScholiaQ45964733MaRDI QIDQ1932108

Domingo Ortiz-Boyer, Nicolás García-Pedrajas

Publication date: 17 January 2013

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2007.12.046

zbMATH Keywords

classificationboostingrandom subspace methodensemble of classifiers

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (7)

An ensemble approach for in silico prediction of Ames mutagenicity ⋮ New two-level ensemble method and its application to chemical compounds properties prediction ⋮ Unnamed Item ⋮ New two-level machine learning method for evaluating the real characteristics of objects ⋮ A noise-detection based AdaBoost algorithm for mislabeled data ⋮ AN ASYMMETRIC ADAPTIVE CLASSIFICATION METHOD ⋮ Ensemble learning based on approximate reducts and bootstrap sampling

Uses Software

• CIXL2
• UCI-ml
• LIBSVM
• C4.5

Cites Work

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• Bagging predictors
• Is combining classifiers with stacking better than selecting the best one?
• Online ensemble learning: An empirical study
• Boosting the margin: a new explanation for the effectiveness of voting methods
• Stacked regressions
• Improved boosting algorithms using confidence-rated predictions
• Approximations of the critical region of the fbietkan statistic
• Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel
• Random forests

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