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ADBIS
1999
Springer
104views Database» more  ADBIS 1999»
13 years 11 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»
14 years 8 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, ...
CARS
2004
13 years 9 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»
14 years 7 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
14 years 8 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...