Compression and Machine Learning: A New Perspective on Feature Space Vectors.
D. SculleyCarla E. BrodleyPublished in: DCC (2006)
Keyphrases
- machine learning
- feature space
- feature vectors
- high dimensional feature space
- dot product
- kernel methods
- feature selection
- mercer kernels
- support vector machine
- image compression
- input data
- compression scheme
- pattern recognition
- machine learning algorithms
- lower dimensional
- mean shift
- kernel function
- high dimensionality
- data compression
- machine learning methods
- learning algorithm
- knowledge acquisition
- image representation
- training samples
- information extraction
- high dimensional
- natural language processing
- supervised learning
- classification accuracy
- explanation based learning
- gaussian kernels
- computer vision
- data mining
- dimension reduction
- compression algorithm
- machine learning approaches
- artificial intelligence
- multiscale
- low dimensional
- computational intelligence
- data points
- decision trees
- image retrieval
- data analysis
- natural language
- reinforcement learning
- visual words
- vector space
- text classification
- dimensionality reduction
- input space
- principal component analysis
- training data
- sample set