Utilizing Local Outlier Factor for Open-Set Classification in High-Dimensional Data - Case Study Applied for Text Documents.
Tomasz WalkowiakSzymon DatkoHenryk MaciejewskiPublished in: IntelliSys (1) (2019)
Keyphrases
- high dimensional data
- text documents
- text classification
- high dimensionality
- text data
- dimensionality reduction
- high dimensional
- nearest neighbor
- low dimensional
- text mining
- text categorization
- subspace clustering
- data points
- similarity search
- pattern recognition
- data sets
- bag of words
- automatic text categorization
- wordnet
- feature selection
- clustering high dimensional data
- image classification
- document clustering
- text clustering
- multivariate temporal data
- supervised learning
- keywords
- machine learning
- topic models
- information extraction
- named entities
- knn
- feature vectors
- clustering algorithm
- real world
- principal component analysis
- classification algorithm
- pairwise
- decision trees
- computer vision