A meta-heuristic density-based subspace clustering algorithm for high-dimensional data.
Parul AgarwalShikha MehtaAjith AbrahamPublished in: Soft Comput. (2021)
Keyphrases
- metaheuristic
- subspace clustering
- high dimensional data
- clustering algorithm
- subspace clusters
- clustering high dimensional data
- simulated annealing
- dimensionality reduction
- tabu search
- search space
- optimization problems
- low dimensional
- high dimensional
- nearest neighbor
- ant colony optimization
- high dimensionality
- genetic algorithm
- data sets
- data analysis
- optimal solution
- dimension reduction
- similarity search
- search methods
- particle swarm optimization
- density based clustering
- original data
- data points
- sparse representation
- dense regions
- high dimensional spaces
- clustering method
- harmony search algorithm
- low rank
- lower dimensional
- k means
- high dimensional datasets
- dimensional data
- high dimensional data sets
- feature space
- arbitrary shape
- subspace learning
- computer vision
- harmony search
- principal component analysis
- image processing
- manifold learning
- database
- data clustering
- linear discriminant analysis
- data mining
- input data
- objective function
- search algorithm
- lower bound