Feature selection using Markov clustering and maximum spanning tree in high dimensional data.
Neha BishtAnnappa BasavaPublished in: IC3 (2016)
Keyphrases
- high dimensional data
- high dimensionality
- dimensionality reduction
- feature selection
- dimension reduction
- low dimensional
- high dimensional
- data points
- nearest neighbor
- high dimensions
- high dimensional data sets
- high dimensional datasets
- subspace clustering
- data sets
- similarity search
- data analysis
- gene expression data
- manifold learning
- linear discriminant analysis
- input space
- high dimensional spaces
- maximum spanning tree
- unsupervised learning
- text categorization
- clustering high dimensional data
- variable selection
- text data
- feature extraction
- clustering algorithm
- feature space
- dimensional data
- machine learning
- support vector
- subspace learning
- neural network
- small sample size
- nonlinear dimensionality reduction
- lower dimensional
- pattern recognition
- feature vectors
- feature set
- data clustering
- microarray data
- input data
- text classification