RMS bounds and sample size considerations for error estimation in linear discriminant analysis.
Amin ZollanvariUlisses M. Braga-NetoEdward R. DoughertyPublished in: GENSiPS (2010)
Keyphrases
- sample size
- error estimation
- small sample size
- model selection
- linear discriminant analysis
- generalization error
- upper bound
- vc dimension
- variance reduction
- worst case
- cross validation
- discriminant analysis
- lower bound
- dimensionality reduction
- null space
- face recognition
- random sampling
- scatter matrices
- dimension reduction
- feature extraction
- principal component analysis
- support vector machine svm
- progressive sampling
- covariance matrix
- high dimensional data
- support vector
- feature selection
- machine learning
- feature space
- least squares
- theoretical guarantees
- computer vision
- neural network
- scatter matrix
- qr decomposition
- data sets