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Using Rough Set to Reduce SVM Classifier Complexity and Its Use in SARS Data Set.

, , , , , and . KES (3), volume 3683 of Lecture Notes in Computer Science, page 575-580. Springer, (2005)

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A Rough Set Based Algorithm for Handling Information Systems where there are a Large Number of Missing Values., , , , and . IICAI, page 2411-2419. IICAI, (2005)Using Positive Region to Reduce the Computational Complexity of Discernibility Matrix Method., , , , , and . IEA/AIE, volume 4031 of Lecture Notes in Computer Science, page 1290-1298. Springer, (2006)Using rough set to induce dependencies between attributes where there are a large amount of missing values: a SARS data application., , and . K-CAP, page 201-202. ACM, (2005)Algorithms for Finding and Correcting Four Kinds of Data Mistakes in Information Table., , , , , and . KES (1), volume 4251 of Lecture Notes in Computer Science, page 714-719. Springer, (2006)Using Rough Set to Reduce SVM Classifier Complexity and Its Use in SARS Data Set., , , , , and . KES (3), volume 3683 of Lecture Notes in Computer Science, page 575-580. Springer, (2005)A SVM Regression Based Approach to Filling in Missing Values., , , , and . KES (3), volume 3683 of Lecture Notes in Computer Science, page 581-587. Springer, (2005)Using Rough Set to Induce All Kinds of Positive Region Knowledge and It's use in SARS Data Set., , , , , and . ICDM (Posters), page 244-252. (2006)A Discretization Algorithm That Keeps Positive Regions of All the Decision Classes., , , , and . KES (1), volume 4251 of Lecture Notes in Computer Science, page 1029-1036. Springer, (2006)Using Rough Set to Induce Comparative Knowledge and Its Use in SARS Data., , , , and . KES (4), volume 3684 of Lecture Notes in Computer Science, page 89-93. Springer, (2005)Using Rough Set to Induce More Abstract Rules from Rule Base., , , , , and . KES (1), volume 4251 of Lecture Notes in Computer Science, page 498-505. Springer, (2006)