A novel random forests-based feature selection method for microarray expression data analysis.
Dengju YaoJing YangXiaojuan ZhanXiaorong ZhanZhiqiang XiePublished in: Int. J. Data Min. Bioinform. (2015)
Keyphrases
- random forests
- microarray
- data analysis
- gene expression levels
- gene expression
- high throughput
- random forest
- microarray data
- clustering analysis
- differential expression
- gene sets
- gene expression data
- ensemble methods
- gene ontology
- logistic regression
- decision trees
- biological data
- machine learning algorithms
- microarray data analysis
- gene expression profiling
- decision tree ensembles
- experimental conditions
- gene selection
- knowledge discovery
- gene expression analysis
- gene networks
- cancer classification
- microarray datasets
- gene expression profiles
- data mining
- transcription factors
- feature subset
- naive bayes
- high dimensional data
- genome wide
- machine learning
- image segmentation
- gene expression datasets
- neural network
- data sets