Unsupervised Artificial Neural Networks for Outlier Detection in High-Dimensional Data.
Daniel PopovicEdouard FouchéKlemens BöhmPublished in: ADBIS (2019)
Keyphrases
- outlier detection
- high dimensional data
- high dimensional datasets
- data sets
- dimensionality reduction
- nearest neighbor
- high dimensional
- high dimensionality
- subspace clustering
- knowledge discovery
- detection algorithm
- low dimensional
- data points
- data analysis
- detecting outliers
- density estimation
- data distribution
- density ratio estimation
- data streams
- low rank
- semi supervised
- neural network
- unsupervised learning
- input space
- similarity search
- dimensional data
- high dimensional spaces
- data mining
- clustering high dimensional data
- detect outliers
- supervised learning
- missing values
- independent component analysis
- training set
- input data
- feature extraction
- computer vision
- text classification