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ADBIS
1999
Springer
104views Database» more  ADBIS 1999»
15 years 1 months ago
Arbiter Meta-Learning with Dynamic Selection of Classifiers and Its Experimental Investigation
In data mining, the selection of an appropriate classifier to estimate the value of an unknown attribute for a new instance has an essential impact to the quality of the classifica...
Alexey Tsymbal, Seppo Puuronen, Vagan Y. Terziyan
ICDE
2006
IEEE
207views Database» more  ICDE 2006»
15 years 11 months ago
Automatic Sales Lead Generation from Web Data
Speed to market is critical to companies that are driven by sales in a competitive market. The earlier a potential customer can be approached in the decision making process of a p...
Ganesh Ramakrishnan, Sachindra Joshi, Sumit Negi, ...
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CARS
2004
14 years 11 months ago
Learning-based pulmonary nodule detection from multislice CT data
An automatic computer-aided detection system is developed for detecting pulmonary nodules from high resolution CT data. The system is based on the concept of machine learning. A ro...
Xiaoguang Lu, Guo-Qing Wei, Jian Zhong Qian, Anil ...
KDD
2001
ACM
216views Data Mining» more  KDD 2001»
15 years 10 months ago
The distributed boosting algorithm
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Aleksandar Lazarevic, Zoran Obradovic
ICPR
2008
IEEE
15 years 10 months ago
Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...