Graph Random Forest: A Graph Embedded Algorithm for Identifying Highly Connected Important Features
Graph Random Forest: A Graph Embedded Algorithm for Identifying Highly Connected Important Features
About this item
Full title
Author / Creator
Tian, Leqi , Wu, Wenbin and Yu, Tianwei
Publisher
Switzerland: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Switzerland: MDPI AG
Subjects
More information
Scope and Contents
Contents
Random Forest (RF) is a widely used machine learning method with good performance on classification and regression tasks. It works well under low sample size situations, which benefits applications in the field of biology. For example, gene expression data often involve much larger numbers of features (p) compared to the size of samples (n). Though...
Alternative Titles
Full title
Graph Random Forest: A Graph Embedded Algorithm for Identifying Highly Connected Important Features
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_e2bf46a5f20e4e97b631b4685556db55
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_e2bf46a5f20e4e97b631b4685556db55
Other Identifiers
ISSN
2218-273X
E-ISSN
2218-273X
DOI
10.3390/biom13071153
