On the Role of Training Data for SVM-Based Microwave Brain Stroke Detection and Classification.
Tomas PokornyJan VrbaOndrej FiserDavid VrbaTomas DrizdalMarek NovákLuca TosiAlessandro PoloMarco SalucciPublished in: Sensors (2023)
Keyphrases
- training data
- support vector machine
- classification accuracy
- decision trees
- support vector
- support vector machine svm
- supervised learning
- class labels
- training set
- svm classifier
- pattern recognition
- feature vectors
- classification algorithm
- training samples
- feature extraction
- classification models
- learning algorithm
- machine learning
- neyman pearson
- pattern classification
- robust detection
- automatic detection
- data sets
- eeg signals
- training dataset
- test data
- training process
- cross validation
- machine learning algorithms
- face recognition
- unseen data
- svm classification
- labelled data
- digital mammograms
- sufficient training data
- event related potentials
- cost sensitive
- human brain
- detection rate
- false positives
- detection algorithm
- image classification
- prior knowledge
- feature space
- feature selection
- neural network