On a solution for the high-dimensionality-small-sample-size regression problem with several different microarrays
by Vladimir Nikulin
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 9, No. 3, 2014

Abstract: A common phenomenon in biological experiments is that it is not possible to obtain complete measurements for all the samples. Note that some microarrays are very informative, but very expensive to have them for all the samples. However, we can use publicly available background knowledge about the potential links between the components of different microarrays (known, also, as genes). As a result, we shall translate all the selected genes in the terms of other genes. Those secondary genes are to be included in the regression models automatically to give the learning processes the right initial directions. The proposed method was tested online during the e-LICO data-mining Contest, where we had achieved second best score.

Online publication date: Tue, 21-Oct-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Mining and Bioinformatics (IJDMB):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com