In:
Applied Mechanics and Materials, Trans Tech Publications, Ltd., Vol. 513-517 ( 2014-02-06), p. 378-381
Abstract:
According to the problem that the linear dimension reduction is not effective to understand gene expression data. using the manifold learning as a guide, analysing dimensionality reduction of gene expression data, selecting colon cancer and leukaemia gene expression datasets for investigation, using inter category distances as the criteria to quantitatively evaluate the effects of data dimensionality reduction. Experiments show that LLE algorithm is more suitable method for the gene expression data. The LLE analyses indicate that there is a clear distinction boundary between the healthy people and the cancer patients.
Type of Medium:
Online Resource
ISSN:
1662-7482
DOI:
10.4028/www.scientific.net/AMM.513-517
DOI:
10.4028/www.scientific.net/AMM.513-517.378
Language:
Unknown
Publisher:
Trans Tech Publications, Ltd.
Publication Date:
2014
detail.hit.zdb_id:
2251882-4
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