Induction of Compact Neural Network Trees through Centroid Based Dimensionality Reduction.
Hirotomo HayashiQiangfu ZhaoPublished in: SMC (2009)
Keyphrases
- dimensionality reduction
- neural network
- compact representations
- oblique decision trees
- pattern recognition
- binary trees
- principal component analysis
- data representation
- high dimensional data
- high dimensional
- feature extraction
- artificial neural networks
- low dimensional
- decision trees
- back propagation
- pattern recognition and machine learning
- inductive learning
- principal components
- neural network model
- feed forward
- constructive induction
- neural network is trained
- feature space
- fuzzy logic
- high dimensionality
- fault diagnosis
- dimensionality reduction methods
- bp neural network
- neural nets
- tree models
- structure preserving
- feature selection
- multidimensional scaling
- kernel pca
- leaf nodes
- network architecture
- prediction model
- self organizing maps
- computer vision
- kernel learning
- learning algorithm
- machine learning
- data points
- nonlinear dimensionality reduction
- rule induction
- multi layer perceptron
- tree structure