A Classification Framework Using Imperfectly Labeled Data for Manufacturing Applications.
Shuo ZhaoXin LiYing-Chi ChenPublished in: ETFA (2020)
Keyphrases
- labeled data
- text classification
- supervised learning
- semi supervised
- class labels
- unlabeled data
- semi supervised classification
- semi supervised learning
- labeled and unlabeled data
- training data
- active learning
- domain adaptation
- transfer learning
- probabilistic boosting tree
- co training
- labeling process
- supervised learning algorithms
- machine learning
- learning algorithm
- multiple instance learning
- training samples
- prior knowledge
- unsupervised learning
- classification accuracy
- support vector
- decision trees
- partially labeled data
- semi supervised learning algorithms
- training set
- label propagation
- data mining
- supervised classification
- supervised classifiers
- data sets
- labeled training data
- information extraction
- document classification
- test data
- feature selection
- data points