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» Generation of Attributes for Learning Algorithms
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ECAI
2008
Springer
15 years 1 months ago
MTForest: Ensemble Decision Trees based on Multi-Task Learning
Many ensemble methods, such as Bagging, Boosting, Random Forest, etc, have been proposed and widely used in real world applications. Some of them are better than others on noisefre...
Qing Wang, Liang Zhang, Mingmin Chi, Jiankui Guo
MLDM
2005
Springer
15 years 4 months ago
Multivariate Discretization by Recursive Supervised Bipartition of Graph
Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...
Sylvain Ferrandiz, Marc Boullé
ICML
2005
IEEE
16 years 3 days ago
Augmenting naive Bayes for ranking
Naive Bayes is an effective and efficient learning algorithm in classification. In many applications, however, an accurate ranking of instances based on the class probability is m...
Harry Zhang, Liangxiao Jiang, Jiang Su
ECAI
2008
Springer
15 years 1 months ago
Online Rule Learning via Weighted Model Counting
Online multiplicative weight-update learning algorithms, such as Winnow, have proven to behave remarkably for learning simple disjunctions with few relevant attributes. The aim of ...
Frédéric Koriche
BMCBI
2006
142views more  BMCBI 2006»
14 years 11 months ago
Improving the Performance of SVM-RFE to Select Genes in Microarray Data
Background: Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. ...
Yuanyuan Ding, Dawn Wilkins