Clustering Analysis for Semi-supervised Learning Improves Classification Performance of Digital Pathology.
Mohammad PeikariJudit T. ZubovitsGina M. ClarkeAnne L. MartelPublished in: MLMI (2015)
Keyphrases
- semi supervised learning
- clustering analysis
- supervised learning
- semi supervised
- semi supervised classification
- improve the classification accuracy
- unsupervised learning
- unlabeled data
- co training
- machine learning
- transductive support vector machine
- labeled data
- semi supervised learning algorithms
- fuzzy clustering
- cluster analysis
- labeled and unlabeled data
- clustering method
- active learning
- data clustering
- training data
- clustering algorithm
- label propagation
- anomaly detection
- classification accuracy
- text categorization
- training set
- k means
- unlabeled samples
- data mining
- feature space
- microarray
- learning algorithm
- pattern recognition
- learning tasks
- transfer learning
- decision boundary
- decision trees
- class labels