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Intelligent Data Engineering and Automated Learning   Syed Zahidur Rashid

Intelligent Data Engineering and Automated Learning

220 страниц. 2015 год.
Scholars' Press
This book investigates the nature of imbalanced data sets and looks at two external methods, which can increase a learner’s performance on under represented classes. Both techniques artificially balance the training data; one by randomly re-sampling examples of the under represented class and adding them to the training set, the other by randomly removing examples of the over represented class from the training set. A combination scheme is then presented. The approach is one in which multiple classifiers are arranged in a hierarchical structure according to their sampling techniques. The architecture consists of two experts, one that boosts performance by combining classifiers that re-sample training data at different rates, the other by combining classifiers that remove data from the training data at different rates. Using the F-measure, which combines precision and recall as a performance statistic, the combination scheme is shown to be effective at learning from severely imbalanced...
 
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