Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/14224
Title: An investigation into the use of gaussian processes for the analysis of microarray data
Authors: SIAH KENG BOON
Keywords: Gaussian Processes, Microarray, Classification, Feature selection
Issue Date: 1-Sep-2004
Source: SIAH KENG BOON (2004-09-01). An investigation into the use of gaussian processes for the analysis of microarray data. ScholarBank@NUS Repository.
Abstract: In this thesis, we have applied Gaussian Processes with Monte Carlo Markov Chain treatment as classification tool, and Automated Relevance Determination (ARD) in Gaussian Processes as feature selection tool for the microarray data. Four datasets, namely Breast cancer, Colon cancer, Leukaemia and Ovarian cancer, are used to study. Filter methods, namely Fisher Score and Information Gain, are used for the first level of feature selection process, before ARD is applied. Comparisons are done upon these two methods. We have found out that these two filter methods, generally, gave comparable results. In the probabilistic framework of Gaussian processes along with ARD parameters, we apply the external cross validation methodology, which gives an unbiased average test accuracy. From the results, the methodology gives encouraging results that are comparable to those in the literature.
URI: http://scholarbank.nus.edu.sg/handle/10635/14224
Appears in Collections:Master's Theses (Open)

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