Parallel classification and feature selection in microarray data using SPRINT.
Lawrence MitchellTerence M. SloanMuriel MewissenPeter GhazalThorsten ForsterMichal PiotrowskiArthur S. TrewPublished in: Concurr. Comput. Pract. Exp. (2014)
Keyphrases
- microarray data
- feature selection
- microarray datasets
- microarray data analysis
- cancer classification
- microarray
- gene selection
- gene expression data
- dna microarray data
- microarray classification
- building classification models
- gene expression profiles
- text classification
- classification accuracy
- gene expression
- small number of samples
- gene expression data sets
- informative features
- high dimensionality
- dna microarray
- gene clusters
- feature space
- feature extraction
- gene expression microarray data
- support vector machine
- feature set
- informative genes
- gene expression analysis
- machine learning
- feature selection algorithms
- text categorization
- support vector
- data sets
- classification models
- colon cancer
- cancer diagnosis
- model selection
- differentially expressed genes
- cluster analysis
- machine learning methods
- gene sets
- feature subset selection
- pattern recognition
- ovarian cancer
- feature vectors
- biologically meaningful
- decision trees
- high dimensional
- microarray gene expression data
- dimensionality reduction
- gene expression patterns
- gene networks
- multi task
- multi class
- training samples
- high throughput
- feature ranking