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» Learning classifiers from only positive and unlabeled data
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KDD
2006
ACM
129views Data Mining» more  KDD 2006»
14 years 9 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
ALT
2010
Springer
13 years 10 months ago
Contrast Pattern Mining and Its Application for Building Robust Classifiers
: The ability to distinguish, differentiate and contrast between different data sets is a key objective in data mining. Such ability can assist domain experts to understand their d...
Kotagiri Ramamohanarao
WWW
2008
ACM
14 years 9 months ago
Can chinese web pages be classified with english data source?
As the World Wide Web in China grows rapidly, mining knowledge in Chinese Web pages becomes more and more important. Mining Web information usually relies on the machine learning ...
Xiao Ling, Gui-Rong Xue, Wenyuan Dai, Yun Jiang, Q...
IJCNN
2007
IEEE
14 years 3 months ago
Random Feature Subset Selection for Analysis of Data with Missing Features
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Joseph DePasquale, Robi Polikar
WWW
2008
ACM
14 years 9 months ago
Online learning from click data for sponsored search
Sponsored search is one of the enabling technologies for today's Web search engines. It corresponds to matching and showing ads related to the user query on the search engine...
Massimiliano Ciaramita, Vanessa Murdock, Vassilis ...