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Combining sampling and ensemble classifier for multiclass imbalance data learning

The aim of this paper is to investigate the effects of combining various sampling and ensemble classifiers on the prediction performance in addressing the multiclass imbalance data learning. This research uses data obtained from the Malaysian medicinal leaf images shape data and three other large be...

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書誌詳細
主要な著者:	Sainin, Mohd Shamrie, Alfred, Rayner, Adnan, Fairuz, Ahmad, Faudziah
フォーマット:	Book Section
出版事項:	Springer 2018
主題:	QA75 Electronic computers. Computer science
オンライン･アクセス:	http://repo.uum.edu.my/25566/ http://doi.org/10.1007/978-981-10-8276-4_25
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

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