Deepak K. Agarwal. Shrinkage estimator generalizations of proximal support vector machines. In KDD '02: Proceedings of the eighth ACM SIGKDD International conference on Knowledge Discovery and Data Mining, pages 173--182, New York, NY, USA, 2002. ACM Press. N. Aronszajn. Theory of reproducing kernels. Transactions of the American Mathematical Society, 68:337--404, May 1950.  Home/Search Document Details and Download
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Classifying Large Data Sets Using SVM with Hierarchical Clusters - Yu, Yang, Han (2003) (1 citation) (Correct)
....to the boundary function, and thus computing an SVM boundary function can be viewed as finding the SVs with the corresponding weights to describe the class boundary. There have been many attempts to revise the original QP formulation such that it can be solved by a QP solver more efficiently [8, 1]. See Section 6 for more details. We do not revise the original QP formulation of SVM. Instead, we try to provide a smaller but high quality data set that is beneficial to computing the SVM boundary function effectively by applying a hierarchical clustering algorithm. Our CB SVM algorithm ....
....for unimportant data and fine summary is made for important data. SVM approximation has been attempted to improve the computational efficiency of SVM by altering the QP formulation to the extent that it keeps a similar semantic of the original SVM while it is faster to be solved by a QP solver [8, 1]. However, their new formulations are still not proven to be efficient and reliable enough to work with very large data sets. On line SVMs or incremental and decremental SVMs have been developed to handle dynamically incoming data efficiently [21, 5, 16] In this senario that an SVMmodel is ....
D. K. Agarwal. Shrinkage estimator generalizations of proximal support vector machines. In Proc. 8th Int. Conf. Knowledge Discovery and Data Mining, Edmonton, Canada, 2002.
Journal of Machine Learning Research 7 (2006).. - Non-Linear.. (Correct)
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Deepak K. Agarwal. Shrinkage estimator generalizations of proximal support vector machines. In KDD '02: Proceedings of the eighth ACM SIGKDD International conference on Knowledge Discovery and Data Mining, pages 173--182, New York, NY, USA, 2002. ACM Press. N. Aronszajn. Theory of reproducing kernels. Transactions of the American Mathematical Society, 68:337--404, May 1950.
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