Enhancing naive classifier for positive unlabeled data based on logistic regression approach.
Mateusz PlatekJan MielniczukPublished in: FedCSIS (2023)
Keyphrases
- logistic regression
- unlabeled data
- labeled training data
- labeled data
- co training
- labeled and unlabeled data
- training data
- semi supervised learning
- decision trees
- semi supervised
- class labels
- training set
- fold cross validation
- naive bayes
- support vector
- training examples
- learning algorithm
- text classification
- supervised learning
- labeled instances
- active learning
- decision boundary
- text categorization
- text classifiers
- bayesian classifiers
- positive and unlabeled examples
- labeled examples
- loss function
- data points
- transfer learning
- positive examples
- feature selection
- training instances
- instance selection
- unsupervised learning
- feature set
- svm classifier
- cost sensitive
- support vector machine
- naive bayes classifier
- learning tasks
- similarity measure
- multi label
- learning problems
- prior knowledge
- bayesian network classifiers
- high dimensional
- feature extraction