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ALT
2004
Springer
15 years 6 months ago
Learning r-of-k Functions by Boosting
We investigate further improvement of boosting in the case that the target concept belongs to the class of r-of-k threshold Boolean functions, which answer “+1” if at least r o...
Kohei Hatano, Osamu Watanabe
LREC
2010
188views Education» more  LREC 2010»
14 years 11 months ago
How Large a Corpus Do We Need: Statistical Method Versus Rule-based Method
We investigate the impact of input data scale in corpus-based learning using a study style of Zipf's law. In our research, Chinese word segmentation is chosen as the study ca...
Hai Zhao, Yan Song, Chunyu Kit
ICML
2004
IEEE
15 years 10 months ago
Learning first-order rules from data with multiple parts: applications on mining chemical compound data
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numa...
ICDAR
2009
IEEE
14 years 7 months ago
Learning Bayesian Networks by Evolution for Classifier Combination
Combining classifier methods have shown their effectiveness in a number of applications. Nonetheless, using simultaneously multiple classifiers may result in some cases in a reduc...
Claudio De Stefano, Francesco Fontanella, Alessand...
ICDM
2007
IEEE
187views Data Mining» more  ICDM 2007»
15 years 4 months ago
A Comparative Study of Methods for Transductive Transfer Learning
The problem of transfer learning, where information gained in one learning task is used to improve performance in another related task, is an important new area of research. While...
Andrew Arnold, Ramesh Nallapati, William W. Cohen