Confusion-based rank similarity filters for computationally-efficient machine learning on high dimensional data.
Katharine A. ShapcottAlex D. BirdPublished in: CoRR (2021)
Keyphrases
- high dimensional data
- computationally efficient
- rank order
- machine learning
- data analysis
- dimensionality reduction
- high dimensional
- low dimensional
- nearest neighbor
- high dimensions
- subspace clustering
- data sets
- data points
- similarity search
- dimension reduction
- high dimensionality
- pattern recognition
- high dimensional data sets
- euclidean distance
- similarity measure
- knowledge discovery
- decision trees
- sparse representation
- data mining
- manifold learning
- lower dimensional
- learning algorithm
- dimensionality curse
- input data
- distance function
- text mining
- nonlinear dimensionality reduction
- high dimensional spaces
- text data
- clustering high dimensional data
- high dimensional datasets
- low rank
- input space
- linear discriminant analysis
- dimensional data
- binary codes
- database
- feature selection
- semi supervised learning
- model selection
- knn
- computational complexity
- active learning
- low dimensional structure