Variance-based Feature Selection for Classification of Cancer Subtypes Using Gene Expression Data.
Aedan G. K. RobertsDaniel R. CatchpoolePaul J. KennedyPublished in: IJCNN (2018)
Keyphrases
- gene expression data
- cancer diagnosis
- gene expression profiles
- feature selection
- cancer classification
- microarray datasets
- gene selection
- dna microarray
- gene expression data sets
- microarray
- gene expression
- microarray data
- colon cancer
- cancer datasets
- high dimensionality
- gene expression datasets
- tumor classification
- dna microarray data
- tissue samples
- gene expression analysis
- gene expression profiling
- microarray gene expression data
- gene regulatory networks
- gene expression data analysis
- microarray data analysis
- data sets
- biologically significant
- classification accuracy
- feature ranking
- support vector
- random forest
- genomic data
- informative genes
- gene expression microarray data
- text classification
- gene expression patterns
- regulatory networks
- analysis of gene expression data
- breast cancer
- high dimensional
- machine learning
- feature space
- feature set
- text categorization
- classification models
- support vector machine svm
- feature selection algorithms
- gene ontology terms
- experimental conditions
- gene networks
- small sample size
- lung cancer
- molecular biology
- biological systems
- cluster analysis
- data mining