Sparse PCA for High-Dimensional Data With Outliers.
Mia HubertTom ReynkensEric SchmittTim VerdonckPublished in: Technometrics (2016)
Keyphrases
- high dimensional data
- sparse pca
- data points
- dimensionality reduction
- low dimensional
- principal component analysis
- nearest neighbor
- high dimensional
- high dimensionality
- feature selection
- similarity search
- data analysis
- data sets
- anomaly detection
- outlier detection
- subspace clustering
- feature space
- dimension reduction
- original data
- lower dimensional
- input space
- principle component analysis
- manifold learning
- distance function
- clustering high dimensional data
- linear discriminant analysis
- input data
- missing data
- sparse representation
- low rank
- variable selection
- semidefinite programming
- euclidean distance
- clustering method
- hyperplane
- image classification
- training set
- feature extraction
- data mining