Classifying Very-High-Dimensional Data with Random Forests of Oblique Decision Trees - researchr publication related

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Thanh-Nghi Do, Philippe Lenca, Stéphane Lallich, Nguyen-Khang Pham. Classifying Very-High-Dimensional Data with Random Forests of Oblique Decision Trees. In Fabrice Guillet, Gilbert Ritschard, Djamel Abdelkader Zighed, Henri Briand, editors, Advances in Knowledge Discovery and Management [Best of EGC 2009, Strasbourg, France]. Volume 292 of Studies in Computational Intelligence, pages 39-55, Springer, 2009. [doi]

The following publications are possibly variants of this publication:

Classifying many-class high-dimensional fingerprint datasets using random forest of oblique decision treesThanh-Nghi Do, Philippe Lenca, Stéphane Lallich. vjcs, 2(1):3-12, 2015. [doi]

Forests of Oblique Decision Stumps for Classifying Very Large Number of TweetsVan T. Le, Thu M. Tran-Nguyen, Khang N. Pham, Nghi T. Do. fdse 2014: 16-28 [doi]

Random ensemble oblique decision stumps for classifying gene expression dataPhuoc-Hai Huynh, Van Hoa Nguyen, Thanh-Nghi Do. soict 2018: 137-144 [doi]

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