Sparse kernel methods for high-dimensional survival data.
Ludger EversClaudia-Martina MessowPublished in: Bioinform. (2008)
Keyphrases
- kernel methods
- high dimensional
- kernel function
- feature space
- survival data
- kernel matrices
- high dimensional data
- low dimensional
- learning problems
- multiple kernel
- high dimensional feature space
- dimensionality reduction
- kernel matrix
- support vector
- machine learning
- similarity search
- high dimensionality
- sparse coding
- survival analysis
- input space
- reproducing kernel hilbert space
- prostate cancer
- data points
- variable selection
- dimension reduction
- high dimensional datasets
- kernel principal component analysis
- positive semi definite
- real world
- nearest neighbor
- support vector machine
- training data
- clinical data
- multiple kernel learning
- kernel pca
- feature extraction
- euclidean space
- learning algorithm
- data mining techniques
- feature vectors
- computer vision
- feature selection
- decision trees