The k-Means Forest Classifier for High Dimensional Data.
Zizhong ChenXin DingShuyin XiaBaiyun ChenPublished in: ICBK (2018)
Keyphrases
- high dimensional data
- k means
- variable weighting
- dimensionality reduction
- high dimensional
- low dimensional
- nearest neighbor
- subspace clustering
- high dimensions
- high dimensionality
- data sets
- data points
- clustering high dimensional data
- similarity search
- dimension reduction
- input data
- training data
- original data
- data analysis
- feature selection
- missing values
- manifold learning
- training samples
- data distribution
- linear discriminant analysis
- feature space
- high dimensional spaces
- clustering algorithm
- high dimensional data sets
- support vector
- clustering method
- svm classifier
- lower dimensional
- variable selection
- training set
- feature set
- high dimensional datasets
- input space
- particle swarm optimizer
- support vector machine
- data clustering
- document clustering
- classification algorithm
- spectral clustering
- cluster analysis
- class labels
- pattern recognition
- multi dimensional
- pairwise
- active learning
- nonlinear dimensionality reduction
- knn
- learning algorithm
- real world