Finding a disease-related gene from microarray data using random forest.
Kazutaka NishiwakiKatsutoshi KanamoriHayato OhwadaPublished in: ICCI*CC (2016)
Keyphrases
- random forest
- cancer classification
- microarray data
- microarray
- gene selection
- differentially expressed genes
- gene sets
- gene expression
- dna microarray
- gene expression data
- fold cross validation
- random forests
- gene clusters
- decision trees
- feature set
- biologically meaningful
- gene networks
- gene expression patterns
- ovarian cancer
- microarray data analysis
- microarray datasets
- gene expression profiles
- feature selection
- cluster analysis
- data sets
- ensemble methods
- gene ontology
- regulatory networks
- biological data
- gene expression analysis
- base classifiers
- multi label
- high throughput
- nearest neighbor
- high dimensional
- image processing
- machine learning algorithms