15 search results - page 1 / 3 » Exploiting Diversity in Ensembles: Improving the Performance... |
MCS
2007
Springer
13 years 4 months ago
2007
Springer
Abstract. Ensembles are often capable of greater predictive performance than any of their individual classifiers. Despite the need for classifiers to make different kinds of err...
MDAI
2005
Springer
13 years 10 months ago
2005
Springer
Combining a set of classifiers has often been exploited to improve the classification performance. Accurate as well as diverse base classifiers are prerequisite to construct a good...
PAKDD
2010
ACM
13 years 6 months ago
2010
ACM
Abstract. One of the more challenging problems faced by the data mining community is that of imbalanced datasets. In imbalanced datasets one class (sometimes severely) outnumbers t...
CEC
2009
IEEE
13 years 8 months ago
2009
IEEE
—When performing predictive data mining, the use of ensembles is known to increase prediction accuracy, compared to single models. To obtain this higher accuracy, ensembles shoul...
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
Bagging is an ensemble method that uses random resampling of a dataset to construct models. In classification scenarios, the random resampling procedure in bagging induces some c...