Novel machine learning approach for classification of high-dimensional microarray data.
Rabia Aziz MusheerC. K. VermaNamita SrivastavaPublished in: Soft Comput. (2019)
Keyphrases
- microarray data
- machine learning
- high dimensional
- feature selection
- small sample size
- building classification models
- microarray
- microarray data analysis
- cancer classification
- gene selection
- gene expression data
- microarray datasets
- gene function prediction
- dna microarray data
- meta analysis
- machine learning methods
- high dimensionality
- gene expression
- pattern recognition
- small number of samples
- gene expression profiles
- informative genes
- data sets
- text classification
- classification accuracy
- decision trees
- cluster analysis
- dna microarray
- microarray classification
- colon cancer
- support vector machine
- microarray gene expression data
- microarray analysis
- gene expression microarray data
- gene expression analysis
- supervised learning
- differentially expressed genes
- unsupervised learning
- cancer diagnosis
- ovarian cancer
- feature vectors
- feature extraction
- learning algorithm
- gene clusters
- gene networks
- feature space
- dimensionality reduction
- support vector
- biologically meaningful
- gene sets
- feature set
- data mining
- training data
- training set
- active learning
- data points
- text mining
- high dimensional data
- support vector machine svm
- database
- model selection