A method for selecting the relevant dimensions for high-dimensional classification in singular vector spaces.
Dawit G. TadesseMark CarpenterPublished in: Adv. Data Anal. Classif. (2019)
Keyphrases
- high dimensional
- classification accuracy
- support vector machine
- pattern classification
- vector space
- dimensional data
- training samples
- machine learning
- neural network
- noisy data
- model selection
- classification algorithm
- intrinsic dimensionality
- dimension reduction
- image classification
- feature set
- pattern recognition
- support vector
- similarity measure
- decision trees