Real-value negative selection over-sampling for imbalanced data set learning-Reference-Cited by-同舟云学术

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Real-value negative selection over-sampling for imbalanced data set learning

Published:2019-09 Issue: Volume:129 Page:118-134
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Tao Xinmin,Li Qing,Ren Chao,Guo Wenjie,Li Chenxi,He Qing,Liu Rui,Zou Junrong

Funder

Fundamental Research Funds for the Central Universities

Harbin science and technology Bureau

Northeast Forestry University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference56 articles.

1. The study of under- and over-sampling methods’ utility in analysis of highly imbalanced data on osteoporosis;Bach;Information Sciences,2017

2. MWMOTE – Majority weighted minority oversampling technique for imbalanced data set learning;Barua;IEEE Trans-actions on Knowledge and Data Engineering,2014

3. Instance selection for classifier performance estimation in meta learning;Blachnik;Entropy,2017

4. Guided undersampling classification for automated radiation therapy quality assurance of prostate cancer treatment;Brown;Medical Physics,2018

5. Rnn-dbscan: A density-based clustering algorithm using reverse nearest neighbor density estimates;Bryant;IEEE Transactions on Knowledge and Data Engineering,2018

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