: A New Approach for Dimension Reduction to Visualize High Dimensional Data.
Frank RehmFrank KlawonnRudolf KrusePublished in: IDA (2005)
Keyphrases
- high dimensional data
- dimension reduction
- low dimensional
- high dimensionality
- dimensionality reduction
- nearest neighbor
- high dimensional
- data sets
- high dimensions
- subspace clustering
- manifold learning
- similarity search
- data points
- data analysis
- linear discriminant analysis
- random projections
- original data
- lower dimensional
- dimensional data
- variable selection
- training data
- high dimensional spaces
- small sample size
- intrinsic dimension
- clustering high dimensional data
- high dimensional data analysis
- input space
- principal component analysis
- preprocessing step
- unsupervised learning
- input data
- object recognition
- decision trees
- dimensionality reduction methods
- feature selection
- learning algorithm
- machine learning
- real world
- neural network