Is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction?
Wray L. BuntineSami PerttuPublished in: AISTATS (2003)
Keyphrases
- dimensionality reduction
- multi faceted
- principal component analysis
- high dimensional data
- principal components analysis
- high dimensionality
- unsupervised learning
- data points
- pattern recognition and machine learning
- subspace projections
- high dimensional
- principal components
- clustering algorithm
- feature extraction
- clustering method
- query intent
- pattern recognition
- linear discriminant analysis
- dimensionality reduction methods
- k means
- feature space
- linear dimensionality reduction
- dimension reduction
- low dimensional
- data representation
- cluster analysis
- random projections
- input space
- multidimensional scaling
- kernel pca
- reduced dimensionality
- lower dimensional
- subspace learning
- dealing with high dimensional data
- manifold learning
- neural network
- covariance matrix
- probabilistic model
- metric learning
- discriminant projection
- sparse representation
- text classification
- principle component analysis
- face recognition
- unsupervised feature selection
- data sets
- machine learning
- feature selection
- face images
- em algorithm
- distance metric
- singular value decomposition
- document clustering
- spectral clustering