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Anglický jazyk
Intelligent Data Engineering and Automated Learning
Autor: Syed Zahidur Rashid
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... Viac o knihe
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O knihe
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 data sets. In fact, when compared to a state of the art combination technique, Adaptive-Boosting, the proposed system is shown to be superior for learning on imbalanced data sets.
- Vydavateľstvo: Scholars' Press
- Rok vydania: 2015
- Formát: Paperback
- Rozmer: 220 x 150 mm
- Jazyk: Anglický jazyk
- ISBN: 9783639762211
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