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.
['Zhan-Li Sun', 'Han Wang', 'Wai-Shing Lau', 'Gerald Seet', 'Danwei Wang', 'Kin-Man Lam']
A novel ensemble algorithm for tumor classification