Random forest for gene selection and microarray data classification
A random forest method has been selected to perform both gene selection and classification of the microarray data. In this embedded method, the selection of smallest possible sets of genes with lowest error rates is the key factor in achieving highest classification accuracy. Hence, improved gene se...
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| Main Authors: | , |
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| Format: | Article |
| Published: |
Springer
2011
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/39857/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3218317/ |
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| Institution: | Universiti Teknologi Malaysia |