Linear Dimensionality Reduction for Margin-Based Classification: High-Dimensional Data and Sensor Networks.
Kush R. VarshneyAlan S. WillskyPublished in: IEEE Trans. Signal Process. (2011)
Keyphrases
- sensor networks
- high dimensional data
- dimensionality reduction
- linear dimensionality reduction
- low dimensional
- high dimensionality
- dimension reduction
- high dimensional
- wireless sensor networks
- pattern classification
- subspace clustering
- pattern recognition
- sensor data
- nearest neighbor
- feature extraction
- feature space
- data streams
- dimensionality reduction methods
- energy consumption
- manifold learning
- sensor nodes
- data points
- data analysis
- original data
- decision trees
- communication cost
- sparse representation
- data distribution
- data sets
- support vector
- clustering high dimensional data
- input space
- similarity search
- communication bandwidth
- random projections
- support vector machine svm
- supervised learning
- principal component analysis
- feature selection
- feature vectors
- lower dimensional
- computer vision
- linear discriminant analysis
- heterogeneous sensor networks
- subspace learning
- machine learning