Error Rates for Kernel Classification under Source and Capacity Conditions.
Hugo CuiBruno LoureiroFlorent KrzakalaLenka ZdeborováPublished in: CoRR (2022)
Keyphrases
- support vector
- feature space
- pattern recognition
- classification systems
- support vector machine svm
- training set
- text classification
- image classification
- machine learning
- neyman pearson
- sufficient conditions
- supervised learning
- classification accuracy
- feature vectors
- kernel machines
- decision trees
- classification scheme
- automatic classification
- classification method
- false positive and false negative
- semi supervised
- support vector machine
- machine learning algorithms
- cross validation
- decision rules
- error rate
- classification rules
- error bounds
- kernel function
- feature extraction
- gaussian processes
- training samples
- model selection
- svm classification
- linearly separable
- data sets