Handling missing values and censored data in PCA of pharmacological matrices.
Jan RamonFabrizio CostaPublished in: KDD Workshop on Statistical and Relational Learning in Bioinformatics (2009)
Keyphrases
- bayesian networks
- missing values
- data matrix
- principal component analysis
- missing entries
- missing data
- matrix completion
- incomplete data
- singular value decomposition
- high dimensional data
- dimensionality reduction
- data imputation
- feature extraction
- principal components
- missing data imputation
- high dimensional
- feature space
- rows and columns
- incomplete data sets
- missing information
- dimension reduction
- imputation methods
- random projections
- negative matrix factorization
- pairwise comparison
- original data
- linear discriminant analysis
- covariance matrix
- face recognition
- sparse matrix
- low rank matrix
- measurement matrix
- feature vectors
- neural network