SVM that maximizes the margin in the input space.
Shotaro AkahoPublished in: Systems and Computers in Japan (2004)
Keyphrases
- input space
- kernel function
- support vector
- support vectors
- training set
- hyperplane
- decision boundary
- maximum margin
- feature space
- knn
- k nearest neighbor
- svm classifier
- support vector machine
- support vector machine svm
- dimensionality reduction
- kernel methods
- regression problems
- high dimension
- data points
- input data
- classification accuracy
- low dimensional
- high dimensional feature space
- linearly separable
- kernel matrix
- high dimensional
- cross validation
- high dimensional data
- feature selection
- structured prediction
- kernel pca
- class labels
- training data
- binary classification
- training examples
- multiple kernel learning
- machine learning
- feature extraction
- linear classifiers
- feature maps
- training samples
- nearest neighbor
- feature vectors
- input patterns
- data sets
- structured output
- output space