Gene Selection from Microarray Data for Alzheimer's Disease Using Random Forest.
Kazutaka NishiwakiKatsutoshi KanamoriHayato OhwadaPublished in: Int. J. Softw. Sci. Comput. Intell. (2017)
Keyphrases
- random forest
- microarray data
- gene selection
- dna microarray
- differentially expressed genes
- cancer classification
- ovarian cancer
- relevant genes
- microarray
- gene sets
- random forests
- decision trees
- gene expression
- microarray classification
- gene expression data
- data sets
- feature set
- high dimensional
- biologically relevant
- microarray data analysis
- feature selection
- dna microarray data
- informative genes
- feature ranking
- cancer diagnosis
- microarray datasets
- cluster analysis
- ensemble methods
- gene expression profiles
- small number of samples
- multi label
- fold cross validation
- microarray analysis
- machine learning
- multi class
- classification accuracy
- biologically meaningful
- data mining techniques
- logistic regression
- base classifiers