A Fast Hybrid Feature Selection Based on Correlation-Guided Clustering and Particle Swarm Optimization for High-Dimensional Data.
Xianfang SongYong ZhangDun-Wei GongXiao-Zhi GaoPublished in: IEEE Trans. Cybern. (2022)
Keyphrases
- high dimensional data
- high dimensionality
- particle swarm optimization
- dimensionality reduction
- feature selection
- dimension reduction
- subspace clustering
- high dimensional
- data points
- low dimensional
- high dimensions
- nearest neighbor
- data sets
- data analysis
- similarity search
- variable weighting
- gene expression data
- high dimensional data sets
- clustering high dimensional data
- high dimensional datasets
- k means
- feature space
- unsupervised learning
- variable selection
- clustering algorithm
- small sample size
- linear discriminant analysis
- multi objective
- data mining
- machine learning
- input space
- microarray data
- feature extraction
- clustering method
- support vector machine
- high dimensional data analysis
- text categorization
- text classification
- subspace learning
- high dimensional spaces
- nonlinear dimensionality reduction
- database
- manifold learning
- learning algorithm
- data clustering
- training data
- input data