A General Study on Feature Selection for Cancer Classification
In the context of cancer research microarray experiments are the most powerful mechanism for the diagnosis of disease. It has the ability to identify the characteristics of gene expression pattern. But DNA microarray experiment produces a huge number of features or genes which is usually more than thousands for a few number of samples or subjects which is less than hundreds.1 To date this problem there are various efficient classification and good feature selection methods are implemented to reduce the complexity and advance the cost. In this paper we on the methodologies for feature selection to identify important genes that improve the accuracy of classification.
How to cite this article:
Bhutia S, Tripathy B. A General Study on Feature Selection for Cancer Classification. J Engr Desg Anal 2020; 3(2): 85-87.
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