A novel ensemble algorithm for tumor classification

A novel ensemble algorithm for tumor classification

From the viewpoint of image processing, a spectral feature-based TLS (Tikhonov-regularized least-squares) ensemble algorithm is proposed for tumor classification using gene expression data. In the TLS model, a test sample is represented as a linear combination of atoms of an overcomplete dictionary....

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Bibliographic Details
Main Authors: Sun, Zhan-Li, Wang, Han, Lau, Wai-Shing, Seet Gim Lee, Gerald, Wang, Danwei, Lam, Kin-Man
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
Subjects:
DRNTU::Engineering::Electrical and electronic engineering
Online Access:https://hdl.handle.net/10356/106080
http://hdl.handle.net/10220/17966
http://dx.doi.org/10.1007/978-3-642-39068-5_36
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Institution: Nanyang Technological University
Language: English
Description
Summary:From the viewpoint of image processing, a spectral feature-based TLS (Tikhonov-regularized least-squares) ensemble algorithm is proposed for tumor classification using gene expression data. In the TLS model, a test sample is represented as a linear combination of atoms of an overcomplete dictionary. Two types of dictionaries, spectral feature-based eigenassays and spectral feature-based metasamples, are proposed for the TLS model. Experimental results on standard databases demonstrate the feasibility and effectiveness of the proposed method.

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