1956 search results - page 71 / 392 » Learning the Relative Importance of Features in Image Data |
JCIT
2010
13 years 3 months ago
2010
With the development of telecom business, customer churn prediction becomes more and more important. An outstanding issue in customer churn prediction is high dimensional problem....
MICCAI
2005
Springer
14 years 9 months ago
2005
Springer
Abstract. In this paper, we propose a new dynamic learning framework that requires a small amount of labeled data in the beginning, then incrementally discovers informative unlabel...
ICIAR
2007
Springer
14 years 2 months ago
2007
Springer
This paper introduces a composite relevance feedback approach for image retrieval using transaction-based and SVM-based learning. A transaction repository is dynamically constructe...
ICANN
2009
Springer
14 years 1 months ago
2009
Springer
Abstract. Many applications of machine learning involve sparse highdimensional data, where the number of input features is (much) larger than the number of data samples, d n. Predi...
KDD
2005
ACM
14 years 9 months ago
2005
ACM
We describe an application of relational knowledge discovery to a key regulatory mission of the National Association of Securities Dealers (NASD). NASD is the world's largest...