Pool-based unsupervised active learning for regression using iterative representativeness-diversity maximization (iRDM).
Ziang LiuXue JiangHanbin LuoWeili FangJiajing LiuDongrui WuPublished in: Pattern Recognit. Lett. (2021)
Keyphrases
- active learning
- semi supervised
- supervised learning
- active sampling
- unsupervised learning
- regression algorithm
- regression model
- data driven
- selective sampling
- learning strategies
- support vector regression
- objective function
- learning process
- imbalanced data classification
- supervised classification
- polynomial regression
- regression problems
- experimental design
- iterative methods
- sample selection
- linear regression
- gaussian processes
- generalization error
- random sampling
- semi supervised learning
- model selection
- least squares
- learning algorithm
- machine learning
- data mining
- unlabeled data
- unsupervised manner
- labeled data
- ridge regression
- artificial neural networks
- training set
- crowd sourced
- pool based active learning