Feature Selection for High Dimensional Data Using Weighted K-Nearest Neighbors and Genetic Algorithm.
Shuangjie LiKaixiang ZhangQianru ChenShuqin WangShaoqiang ZhangPublished in: IEEE Access (2020)
Keyphrases
- high dimensional data
- k nearest neighbor
- nearest neighbor
- feature selection
- knn
- genetic algorithm
- high dimensionality
- dimensionality reduction
- text categorization
- dimension reduction
- high dimensional
- similarity search
- distance function
- text classification
- manifold learning
- data points
- input space
- subspace clustering
- neural network
- clustering high dimensional data
- high dimensional spaces
- data sets
- support vector machine
- support vector machine svm
- machine learning
- low dimensional
- index structure
- data distribution
- feature extraction
- nearest neighbor search
- variable selection
- small sample size
- feature space
- k nearest
- nonlinear dimensionality reduction
- dimensional data
- support vector
- training set
- linear discriminant analysis
- classification algorithm
- data analysis
- sparse representation
- high dimensional data sets
- feature set
- pattern recognition
- particle swarm optimization
- missing values
- input data