Neutral network learning algorithms for microarray classification

Neutral network learning algorithms for microarray classification

In this thesis, we focus on two supervised machine learning algorithms in cancer classification, namely the Backpropagation algorithm (BP) and Extreme Learning Machine algorithm (ELM). The objective of this project is to determine the best generalization network for BP and ELM for microarray data an...

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Main Author: Shwe, Sin Aung.
Other Authors: Saratchandran, Paramasivan
Format: Theses and Dissertations
Published: 2008
Subjects:
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:http://hdl.handle.net/10356/3256
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Institution: Nanyang Technological University
id sg-ntu-dr.10356-3256
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spelling sg-ntu-dr.10356-32562023-07-04T15:53:15Z Neutral network learning algorithms for microarray classification Shwe, Sin Aung. Saratchandran, Paramasivan School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems In this thesis, we focus on two supervised machine learning algorithms in cancer classification, namely the Backpropagation algorithm (BP) and Extreme Learning Machine algorithm (ELM). The objective of this project is to determine the best generalization network for BP and ELM for microarray data analysis for three problems, namely "ALL-AML" Leukemia, Colon Tumor and Primate Splice Junction's gene sequence. Master of Science (Computer Control and Automation) 2008-09-17T09:25:40Z 2008-09-17T09:25:40Z 2005 2005 Thesis http://hdl.handle.net/10356/3256 Nanyang Technological University application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
topic DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Shwe, Sin Aung.
Neutral network learning algorithms for microarray classification
description In this thesis, we focus on two supervised machine learning algorithms in cancer classification, namely the Backpropagation algorithm (BP) and Extreme Learning Machine algorithm (ELM). The objective of this project is to determine the best generalization network for BP and ELM for microarray data analysis for three problems, namely "ALL-AML" Leukemia, Colon Tumor and Primate Splice Junction's gene sequence.
author2 Saratchandran, Paramasivan
author_facet Saratchandran, Paramasivan
Shwe, Sin Aung.
format Theses and Dissertations
author Shwe, Sin Aung.
author_sort Shwe, Sin Aung.
title Neutral network learning algorithms for microarray classification
title_short Neutral network learning algorithms for microarray classification
title_full Neutral network learning algorithms for microarray classification
title_fullStr Neutral network learning algorithms for microarray classification
title_full_unstemmed Neutral network learning algorithms for microarray classification
title_sort neutral network learning algorithms for microarray classification
publishDate 2008
url http://hdl.handle.net/10356/3256
_version_ 1772828417205469184

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