An imbalanced data classification algorithm of improved autoencoder neural network

Imbalanced data classification problem has always been a hotspot in the field of machine learning research. Pointing to the overfitting and noise problems of oversampling algorithm when synthesizing new minority class samples, the current study proposed a stacked denoising autoencoder neural network...

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Vydané v:	2016 Eighth International Conference on Advanced Computational Intelligence (ICACI) s. 95 - 99
Hlavní autori:	Chenggang Zhang, Wei Gao, Jiazhi Song, Jinqing Jiang
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.02.2016
Predmet:	Biological neural networks Cancer classification Classification algorithms cost sensitive imbalanced data Machine learning algorithms Noise reduction oversampling stacked denoising autoencoder neural network Training
ISBN:	9781467377805, 1467377805
On-line prístup:	Získať plný text
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