Recursive Cluster Elimination based Rank Function (SVM-RCE-R) implemented in KNIME [version 2; peer review: 1 approved, 2 approved with reservations]
In our earlier study, we proposed a novel feature selection approach, Recursive Cluster Elimination with Support Vector Machines (SVM-RCE) and implemented this approach in Matlab. Interest in this approach has grown over time and several researchers have incorporated SVM-RCE into their studies, resu...
Main Authors: | Malik Yousef, Burcu Bakir-Gungor, Amhar Jabeer, Gokhan Goy, Rehman Qureshi, Louise C. Showe |
---|---|
Format: | Article |
Language: | English |
Published: |
F1000 Research Ltd
2021-01-01
|
Series: | F1000Research |
Online Access: | https://f1000research.com/articles/9-1255/v2 |
Similar Items
-
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
by: Showe Louise C, et al.
Published: (2007-05-01) -
miRcorrNet: machine learning-based integration of miRNA and mRNA expression profiles, combined with feature grouping and ranking
by: Malik Yousef, et al.
Published: (2021-05-01) -
miRdisNET: Discovering microRNA biomarkers that are associated with diseases utilizing biological knowledge-based machine learning
by: Amhar Jabeer, et al.
Published: (2023-01-01) -
Discovering Potential Taxonomic Biomarkers of Type 2 Diabetes From Human Gut Microbiota via Different Feature Selection Methods
by: Burcu Bakir-Gungor, et al.
Published: (2021-08-01) -
microBiomeGSM: the identification of taxonomic biomarkers from metagenomic data using grouping, scoring and modeling (G-S-M) approach
by: Burcu Bakir-Gungor, et al.
Published: (2023-11-01)