Supervised Learning via Unsupervised Sparse Autoencoder

Supervised Learning via Unsupervised Sparse Autoencoder

Dimensionality reduction is commonly used to preprocess high-dimensional data, which is an essential step in machine learning and data mining. An outstanding low-dimensional feature can improve the efficiency of subsequent learning tasks. However, existing methods of dimensionality reduction mostly...

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Bibliographic Details
Main Authors: Jianran Liu, Chan Li, Wenyuan Yang
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Machine learning
dimensionality reduction
sparse autoencoder
supervised learning
feature representation
Online Access:https://ieeexplore.ieee.org/document/8558569/

Internet

https://ieeexplore.ieee.org/document/8558569/

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