Comparisons among several methods for handling missing data in principal component analysis (PCA).
Sébastien LoiselYoshio TakanePublished in: Adv. Data Anal. Classif. (2019)
Keyphrases
- principal component analysis
- missing data
- missing values
- incomplete data
- dimension reduction methods
- feature extraction
- principal components
- dimension reduction
- independent component analysis
- linear discriminant analysis
- dimensionality reduction
- computer vision
- covariance matrix
- structure from motion
- incomplete information
- semi supervised
- support vector machine
- feature space
- negative matrix factorization
- principle component analysis