A comparative study of nature-inspired metaheuristic algorithms using a three-phase hybrid approach for gene selection and classification in high-dimensional cancer datasets.
Shilan S. HameedWan Haslina HassanLiza Abdul LatiffFahmi F. MuhammadPublished in: Soft Comput. (2021)
Keyphrases
- cancer classification
- cancer datasets
- gene selection
- gene expression data
- microarray data
- microarray
- high dimensional
- cancer diagnosis
- high dimensionality
- microarray datasets
- feature selection
- gene expression
- gene expression profiles
- random forest
- informative genes
- support vector machine svm
- dna microarray
- metaheuristic
- neural network
- data sets
- ant colony optimization
- feature space
- feature ranking
- evolutionary algorithm
- swarm intelligence
- classification accuracy
- high dimensional data
- text classification
- low dimensional
- support vector machine
- data points