Principal Component Analysis (PCA) for estimating chlorophyll concentration using Forward and generalized Regression Neural Networks.
Mohammad Zounemat-KermaniPublished in: Appl. Artif. Intell. (2014)
Keyphrases
- principal component analysis
- neural network
- principal components
- partial least squares
- spectral data
- dimensionality reduction
- covariance matrix
- linear discriminant analysis
- dimension reduction
- discriminant analysis
- independent component analysis
- face recognition
- low dimensional
- regression model
- artificial neural networks
- feature extraction
- classification and regression trees
- genetic algorithm
- pattern recognition
- feature space
- back propagation
- face images
- fuzzy logic
- kernel pca
- neural classifier
- water quality
- lower dimensional
- negative matrix factorization
- support vector regression
- face databases
- neural network model
- model selection
- subspace learning
- correlation coefficient
- training procedure
- regression algorithm
- singular value decomposition
- high dimensional
- kernel principal component analysis
- principle component analysis
- feature selection