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Combining bagging, boosting, rotation forest and random subspace methods

. Artificial Intelligence Review, (2011)

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Predicting Students' Performance In Distance Learning Using Machine Learning Techniques., , and . Appl. Artif. Intell., 18 (5): 411-426 (2004)Local reweight wrapper for the problem of imbalance.. Int. J. Artif. Intell. Soft Comput., 1 (1): 25-38 (2008)Combining bagging, boosting, rotation forest and random subspace methods. Artificial Intelligence Review, (2011)Bagged Averaging of Regression Models., , and . AIAI, volume 204 of IFIP, page 53-60. Springer, (2006)A random subspace method that uses different instead of similar models for regression and classification problems.. IJIDS, 3 (2): 173-188 (2011)Local Bagging of Decision Stumps., , and . IEA/AIE, volume 3533 of Lecture Notes in Computer Science, page 406-411. Springer, (2005)Increasing the Classification Accuracy of Simple Bayesian Classifier., and . AIMSA, volume 3192 of Lecture Notes in Computer Science, page 198-207. Springer, (2004)A combinational incremental ensemble of classifiers as a technique for predicting students' performance in distance education., , and . Knowl. Based Syst., 23 (6): 529-535 (2010)Intelligent Systems and Knowledge Management (Part II)., , and . J. Comput. Methods Sci. Eng., 11 (3): 89-90 (2011)Locally application of cascade generalization for classification problems.. Intell. Decis. Technol., 2 (4): 239-246 (2008)