Informative Feature Clustering and Selection for Gene Expression Data

Informative Feature Clustering and Selection for Gene Expression Data

Feature selection aims to remove irrelevant and redundant features from input data. For gene expression, selecting important genes from gene expression data is essential since the gene expression data often consists of a large number of genes. However, the commonly-used feature selection methods are...

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Bibliographic Details
Main Authors: Yuqi Yang, Pengshuai Yin, Zhihang Luo, Wenwen Gu, Renjie Chen, Qingyao Wu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Feature selection
co-clustering
stratification
classification
Online Access:https://ieeexplore.ieee.org/document/8894465/

Internet

https://ieeexplore.ieee.org/document/8894465/

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