In this project, we target to find effective and unsupervised feature reduction tools for gene expression data classification purpose. We have tackled the problem from both feature selection and feature extraction approaches. Three feature reduction algo- rithms, fast entropy ranking, revised locally linear embedding, and feature grouping are proposed, analyzed and tested on several microarray datasets.MASTER OF ENGINEERING (EEE
Microarray analysis and visualization is very helpful for biologists and clinicians to understand ge...
A general framework for microarray data classification is proposed in this paper. It pro-duces preci...
A subset of features from a large data set is sufficient to improve the classifier performance in th...
We summarise various ways of performing dimensionality reduction on high-dimensional microarray data...
© 2015 Zena M. Hira and Duncan F. Gillies.We summarise various ways of performing dimensionality red...
Abstract Dimension reduction is an important issue for analysis of gene expression microarray data, ...
When gene expression data are too large to be processed, they are transformed into a reduced represe...
73 p.Cancer classification is one of the most important applications in microarray data analy-sis. D...
Thousands of genes can be identified by DNA microarray technology at the same time which can have a ...
Motivation: The microarray report measures the expressions of tens of thousands of genes, producing ...
Abstract The recent technology development in the concern of microarray experiments has provided man...
Abstract: Data mining played vital role in comprehending, analyzing, understanding and interpreting ...
A plenitude of feature selection (FS) methods is available in the literature, most of them rising as...
Recently, feature selection and dimensionality reduction have become fundamental tools for many data...
Microarray technology has become an emerging trend in the domain of genetic research in which many r...
Microarray analysis and visualization is very helpful for biologists and clinicians to understand ge...
A general framework for microarray data classification is proposed in this paper. It pro-duces preci...
A subset of features from a large data set is sufficient to improve the classifier performance in th...
We summarise various ways of performing dimensionality reduction on high-dimensional microarray data...
© 2015 Zena M. Hira and Duncan F. Gillies.We summarise various ways of performing dimensionality red...
Abstract Dimension reduction is an important issue for analysis of gene expression microarray data, ...
When gene expression data are too large to be processed, they are transformed into a reduced represe...
73 p.Cancer classification is one of the most important applications in microarray data analy-sis. D...
Thousands of genes can be identified by DNA microarray technology at the same time which can have a ...
Motivation: The microarray report measures the expressions of tens of thousands of genes, producing ...
Abstract The recent technology development in the concern of microarray experiments has provided man...
Abstract: Data mining played vital role in comprehending, analyzing, understanding and interpreting ...
A plenitude of feature selection (FS) methods is available in the literature, most of them rising as...
Recently, feature selection and dimensionality reduction have become fundamental tools for many data...
Microarray technology has become an emerging trend in the domain of genetic research in which many r...
Microarray analysis and visualization is very helpful for biologists and clinicians to understand ge...
A general framework for microarray data classification is proposed in this paper. It pro-duces preci...
A subset of features from a large data set is sufficient to improve the classifier performance in th...
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