Classification Of Microarray Datasets Using Random Forest
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Date
2009-06
Authors
Ng, Ee Ling
Journal Title
Journal ISSN
Volume Title
Publisher
Universiti Sains Malaysia
Abstract
DNA microarray technology has enabled the capability to monitor the
expressions of tens of thousands of genes in a biological sample on a single chip.
Medical fields can benefit from microarray data mining as it helps in early detection of genes mutation and diagnosis of disease. A well built model can be used to predict unknown disease classes in a test case. Prior to a well built model is to achieve good
classification results which rely very much on the classifiers that are being used.
However, in most microarray data, the number of genes usually outnumbers the number
of samples.
Description
Keywords
Microarray , Random Forest