A novel approach to estimation of E. coli promoter gene sequences: Combining feature selection and least square support vector machine (FS_LSSVM).
Kemal PolatSalih GünesPublished in: Appl. Math. Comput. (2007)
Keyphrases
- feature selection
- ls svm
- least squares support vector machine
- escherichia coli
- gene expression data
- support vector machine
- transcription factor binding sites
- genomic sequences
- gene regulatory networks
- small sample
- gene expression
- parameter estimation
- support vector
- feature set
- least squares
- hidden markov models
- variable selection
- microarray data
- high dimensionality
- machine learning
- microarray
- feature extraction
- metabolic pathways
- dimensionality reduction
- model selection
- cis regulatory
- decision trees
- training data
- feature space
- feature selection algorithms
- generalization ability
- dna sequences
- biological data
- rbf neural network
- image classification
- hyperparameters
- cross validation
- feature subset
- correlation coefficient
- prior information