Under-Sampling and Feature Selection Algorithms for S2SMLP

Under-Sampling and Feature Selection Algorithms for S2SMLP

Imbalance learning is a hot topic in the data mining and machine learning domains. Data-level, algorithm-level and ensemble solutions are the three main methods proposed thus far to address imbalance learning. To alleviate the issues of data explosion and feature selection in multilayer perceptron b...

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Bibliographic Details
Main Authors: Shudong Liu, Ke Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Multilayer perceptron
under-sampling
spectral clustering
imbalance learning
feature selection
information gain
Online Access:https://ieeexplore.ieee.org/document/9233461/

Internet

https://ieeexplore.ieee.org/document/9233461/

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