Conference Paper

A Novel Visualization Classifier and Its Applications.

DOI: 10.1007/11540007_157 Conference: Fuzzy Systems and Knowledge Discovery, Second International Conference, FSKD 2005, Changsha, China, August 27-29, 2005, Proceedings, Part II
Source: DBLP

ABSTRACT Classifiers, as one of the important tools of analyzing gene expression data in the post-genomic epoch, have been used widely
in the classification of different cancer types in the past few years. Although most existing classifiers have high classification
accuracy, the process of classification is a black box and they can not give biologists more information and interpretable
results of classification. In this paper, we propose a novel visualization cancer classification method. Besides offering
high classification accuracy, the method can help us identify complex disease-related genes and assess gene expression variation
during the process of classification. The results of classification are natural and interpretable and the process of classification
is visible. To evaluate the performance of the method we have applied the proposed method to three public data sets. The experimental
results demonstrate that the approach is feasible and useful.

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