A review of feature set partitioning methods for multi-view ensemble learning-Reference-Cited by-同舟云学术

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A review of feature set partitioning methods for multi-view ensemble learning

Published:2023-12 Issue: Volume:100 Page:101959
ISSN:1566-2535
Container-title:Information Fusion
language:en
Short-container-title:Information Fusion

Author:

Kumar Aditya^ORCID,Yadav Jainath

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Signal Processing,Software

Reference201 articles.

1. Challenges of big data analysis;Fan;Natl. Sci. Rev.,2014

2. Big data: A review;Sagiroglu,2013

3. Big data: challenges, opportunities, and realities;Bhadani,2016

4. Data mining for internet of things: A survey;Tsai;IEEE Commun. Surv. Tutor.,2013

5. The curse of dimensionality in data mining and time series prediction;Verleysen,2005

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1. Minimum spanning tree clustering approach for effective feature partitioning in multi-view ensemble learning;Knowledge and Information Systems;2024-07-18

2. Multi-view Stacked CNN-BiLSTM (MvS CNN-BiLSTM) for urban PM2.5 concentration prediction of India’s polluted cities;Journal of Cleaner Production;2024-03

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