Feature Selection for Supervised Learning and Compression.
Phillip TaylorNathan GriffithsVince HallZhou XuAlex MouzakitisPublished in: Appl. Artif. Intell. (2022)
Keyphrases
- supervised learning
- feature selection
- unsupervised learning
- supervised and unsupervised learning
- machine learning
- text categorization
- image compression
- learning algorithm
- data compression
- training data
- active learning
- compression ratio
- semi supervised
- feature selection algorithms
- instance selection
- mutual information
- compression scheme
- learning tasks
- training set
- compression algorithm
- data reduction
- information gain
- learning problems
- dimensionality reduction
- feature set
- feature extraction
- semi supervised learning
- classification accuracy
- unlabeled data
- support vector
- reinforcement learning
- classification models
- feature subset
- feature construction
- accurate classification
- naive bayes
- training samples
- multi task
- compression rate
- discriminative features
- selected features
- method for feature selection
- generalization error
- statistical learning
- feature space
- text classification
- multi class
- labeled data
- multiple instance learning
- feature weighting
- small sample
- high dimensionality
- unsupervised feature selection
- model selection