Impact of Clustering on a Synthetic Instance Generation in Imbalanced Data Streams Classification.
Ireneusz CzarnowskiDenis Mayr Lima MartinsPublished in: ICCS (1) (2022)
Keyphrases
- data streams
- support vector
- classification accuracy
- clustering algorithm
- pattern recognition
- unsupervised classification
- unsupervised clustering
- high dimensionality
- class imbalance
- machine learning
- unsupervised learning
- classification algorithm
- clustering method
- text classification
- classification models
- supervised classification
- feature vectors
- decision trees
- pattern classification
- clustering analysis
- single class
- outlier detection
- sliding window
- class labels
- feature extraction
- k means
- support vector machine
- sensor networks
- image classification
- model selection
- supervised learning
- concept drift
- cost sensitive
- streaming data
- nearest neighbor
- active learning
- stream data
- binary classification problems
- imbalanced datasets
- self organizing maps
- data stream classification
- imbalanced class distribution
- multiple data streams