Följ
Ying Yang
Ying Yang
Australian Taxation Office
Verifierad e-postadress på ato.gov.au
Titel
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Discretization for naive-Bayes learning: managing discretization bias and variance
Y Yang, GI Webb
Machine learning 74 (1), 39-74, 2009
2482009
A comparative study of discretization methods for naive-bayes classifiers
Y Yang, GI Webb
Proceedings of PKAW 2002, 2002
2402002
Combining proactive and reactive predictions for data streams
Y Yang, X Wu, X Zhu
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005
1572005
Proportional k-interval discretization for naive-Bayes classifiers
Y Yang, GI Webb
European Conference on Machine Learning, 564-575, 2001
1512001
Discretization methods
Y Yang, GI Webb, X Wu
Data mining and knowledge discovery handbook, 101-116, 2009
1372009
Mining in anticipation for concept change: Proactive-reactive prediction in data streams
Y Yang, X Wu, X Zhu
Data mining and knowledge discovery 13 (3), 261-289, 2006
1252006
On why discretization works for naive-bayes classifiers
Y Yang, GI Webb
Australasian Joint Conference on Artificial Intelligence, 440-452, 2003
1252003
Adapted one-versus-all decision trees for data stream classification
S Hashemi, Y Yang, Z Mirzamomen, M Kangavari
IEEE Transactions on Knowledge and Data Engineering 21 (5), 624-637, 2008
1202008
Dynamic classifier selection for effective mining from noisy data streams
X Zhu, X Wu, Y Yang
Fourth IEEE International Conference on Data Mining (ICDM'04), 305-312, 2004
1142004
Flexible decision tree for data stream classification in the presence of concept change, noise and missing values
S Hashemi, Y Yang
Data Mining and Knowledge Discovery 19 (1), 95-131, 2009
842009
Error detection and impact-sensitive instance ranking in noisy datasets
X Zhu, X Wu, Y Yang
AAAI, 378-384, 2004
772004
Weighted proportional k-interval discretization for naive-bayes classifiers
Y Yang, GI Webb
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 501-512, 2003
632003
To select or to weigh: A comparative study of linear combination schemes for superparent-one-dependence estimators
Y Yang, GI Webb, J Cerquides, KB Korb, J Boughton, KM Ting
IEEE Transactions on Knowledge and Data Engineering 19 (12), 1652-1665, 2007
572007
Ensemble selection for superparent-one-dependence estimators
Y Yang, K Korb, KM Ting, GI Webb
Australasian Joint Conference on Artificial Intelligence, 102-112, 2005
552005
Effective classification of noisy data streams with attribute-oriented dynamic classifier selection
X Zhu, X Wu, Y Yang
Knowledge and Information Systems 9 (3), 339-363, 2006
472006
Classifying under computational resource constraints: anytime classification using probabilistic estimators
Y Yang, G Webb, K Korb, KM Ting
Machine Learning 69 (1), 35-53, 2007
452007
Discretization for naive-bayes learning
Y Yang
Monash University, 2003
452003
Dealing with predictive-but-unpredictable attributes in noisy data sources
Y Yang, X Wu, X Zhu
European Conference on Principles of Data Mining and Knowledge Discovery …, 2004
442004
A lazy bagging approach to classification
X Zhu, Y Yang
Pattern Recognition 41 (10), 2980-2992, 2008
412008
Incremental discretization for naïve-bayes classifier
J Lu, Y Yang, GI Webb
International Conference on Advanced Data Mining and Applications, 223-238, 2006
372006
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Artiklar 1–20