@inproceedings{8af9e78b4e634db1b6da908b40448f49,
title = "ε-tube based pattern selection for support vector machines",
abstract = "The training time complexity of Support Vector Regression (SVR) is O(N 3). Hence, it takes long time to train a large dataset. In this paper, we propose a pattern selection method to reduce the training time of SVR. With multiple bootstrap samples, we estimate ε-tube. Probabilities are computed for each pattern to fall inside ε-tube. Those patterns with higher probabilities are selected stochastically. To evaluate the new method, the experiments for 4 data-sets have been done. The proposed method resulted in the best performance among all methods, and even its performance was found stable.",
author = "Dongil Kim and Sungzoon Cho",
year = "2006",
doi = "10.1007/11731139_26",
language = "English",
isbn = "3540332065",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "215--224",
booktitle = "Advances in Knowledge Discovery and Data Mining - 10th Pacific-Asia Conference, PAKDD 2006, Proceedings",
note = "10th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2006 ; Conference date: 09-04-2006 Through 12-04-2006",
}