Gene selection and classification approach for microarray data based on Random Forest Ranking and BBHA.
Elnaz PashaeiMustafa OzenNizamettin AydinPublished in: BHI (2016)
Keyphrases
- cancer classification
- random forest
- gene selection
- microarray data
- feature ranking
- microarray
- cancer diagnosis
- colon cancer
- relevant genes
- gene expression data
- decision trees
- informative genes
- dna microarray
- feature selection
- gene expression
- microarray data analysis
- microarray datasets
- random forests
- gene expression profiles
- dna microarray data
- microarray classification
- feature set
- microarray analysis
- ovarian cancer
- data sets
- high dimensional
- fold cross validation
- gene sets
- cluster analysis
- differentially expressed genes
- biologically relevant
- small number of samples
- selected genes
- experimental conditions
- ensemble learning
- ensemble methods
- image classification
- classification accuracy
- base classifiers
- high dimensionality
- feature vectors
- feature space
- support vector
- training data
- learning algorithm