Feature selection based on artificial bee colony and gradient boosting decision tree
Data from many real-world applications can be high dimensional and features of such data are usually highly redundant. Identifying informative features has become an important step for data mining to not only circumvent the curse of dimensionality but to reduce the amount of data for processing. In...
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Published in | Applied soft computing Vol. 74; pp. 634 - 642 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.01.2019
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Subjects | |
Online Access | Get full text |
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