A Feature Extraction Method Based on Stacked Denoising Autoencoder for Massive High Dimensional Data.
Baoding XuXiangqian DingRuichun HouCheng ZhuPublished in: ICNC-FSKD (2018)
Keyphrases
- high dimensional data
- denoising
- data analysis
- dimensionality reduction
- high dimensional
- low dimensional
- high dimensionality
- nearest neighbor
- subspace clustering
- high dimensions
- dimension reduction
- data points
- original data
- data sets
- similarity search
- linear discriminant analysis
- image processing
- data distribution
- missing values
- manifold learning
- input space
- preprocessing step
- dimensional data
- high dimensional spaces
- total variation
- high dimensional datasets
- lower dimensional
- nonlinear dimensionality reduction
- clustering high dimensional data
- sparse representation
- natural images
- input data
- principal component analysis
- pattern recognition
- decision trees
- text data
- wavelet packet
- feature vectors
- small sample size
- high dimensional data sets
- neural network