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An Extended Study of the Discriminant Random Forest.

, , , and . Data Mining, volume 8 of Annals of Information Systems, Springer, (2010)

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Discriminant Random Forests., , , , , , and . DMIN, page 55-61. CSREA Press, (2008)Practical Ensemble Classification Error Bounds for Different Operating Points., , , , and . IEEE Trans. Knowl. Data Eng., 25 (11): 2590-2601 (2013)Improved MLP structures for data-driven feature extraction for ASR., , , and . INTERSPEECH, page 2129-2132. ISCA, (2005)Using MLP features in SRI's conversational speech recognition system., , , and . INTERSPEECH, page 2141-2144. ISCA, (2005)Class-specific error bounds for ensemble classifiers., , , , and . KDD, page 843-852. ACM, (2010)Tandem Connectionist Feature Extraction for Conversational Speech Recognition., , , and . MLMI, volume 3361 of Lecture Notes in Computer Science, page 223-231. Springer, (2004)Robust ASR front-end using spectral-based and discriminant features: experiments on the Aurora tasks., , , , , , , , , and . INTERSPEECH, page 429-432. ISCA, (2001)Feature transformations and combinations for improving ASR performance., , and . INTERSPEECH, page 477-480. ISCA, (2003)Improvements to Context Based Self-Supervised Learning., , and . CVPR, page 9339-9348. Computer Vision Foundation / IEEE Computer Society, (2018)Building ultra-low false alarm rate Support Vector Classifier ensembles using Random Subspaces., , and . CIDM, page 1-8. IEEE, (2009)