2007 IEEE 7th International Symposium on BioInformatics and BioEngineering

Format:

Book

Author/Creator:

Institute of Electrical and Electronics Engineers, author, issuing body.

Contributor:

IEEE Staff, Contributor.

Language:

English

Subjects (All):

Bioinformatics--Congresses.

Bioinformatics.

Physical Description:

1 online resource

Place of Publication:

[Place of publication not identified] I E E E 2007

Language Note:

English

Summary:

Dimension reduction plays an important role in handling the massive quantity of high dimensional data such as biomedical text data, gene expression data, and mass spectrometry data, and so forth. In this paper, we introduce distance preserving dimension reduction (DPDR) based on the QR factorization (DPDR/QR) or the Cholesky factorization (DPDR/C). DPDR generates lower dimensional representations of the high-dimensional data, which can exactly preserve Euclidean distances and cosine similarities between any pair of data points in the original dimensional space. After projecting data points to the lower dimensional space obtained from DPDR, one can execute other data analysis algorithms. DPDR can substantially reduce the computing time and/or memory requirement of a given data analysis algorithm, especially when we need to run the data analysis algorithm many times for estimating parameters or searching for a better solution.

Notes:

Bibliographic Level Mode of Issuance: Monograph

ISBN:

9781509088072

1509088075