On Dimensionality, Sample Size, Classification Error, and Complexity of Classification Algorithm in Pattern Recognition.
Sarunas RaudysVitalijus PikelisPublished in: IEEE Trans. Pattern Anal. Mach. Intell. (1980)
Keyphrases
- classification algorithm
- sample size
- classification error
- class labels
- generalization error
- training set
- pattern recognition
- hyperparameters
- worst case
- model selection
- random sampling
- upper bound
- dimensionality reduction
- learning algorithm
- knn
- cross validation
- k nearest neighbor
- high dimensional
- support vector machine
- covariance matrix
- feature space
- naive bayes
- training samples
- image processing
- training data
- machine learning
- labeled data
- feature extraction
- classification rules
- base classifiers
- estimation error
- neural network
- decision rules
- supervised learning
- computer vision
- active learning
- data mining
- text classification
- lower bound
- classification accuracy