A programming paradigm for machine learning, with a case study of Bayesian networks.
Lloyd AllisonPublished in: ACSC (2006)
Keyphrases
- bayesian networks
- machine learning
- pattern recognition
- programming language
- inductive learning
- machine learning methods
- feature selection
- declarative programming
- programming paradigms
- learning bayesian networks
- programming environment
- structure learning
- conditional independence
- machine learning algorithms
- case study
- computer vision
- machine learning approaches
- probabilistic inference
- test bed
- text mining
- learning systems
- data mining
- statistical learning
- artificial intelligence
- learning tasks
- semi supervised learning
- inference in bayesian networks
- supervised learning
- information extraction
- learning algorithm
- computer science
- graphical models
- conditional probabilities
- inductive logic programming
- data analysis
- probabilistic classifiers
- support vector machine
- probabilistic reasoning
- probabilistic knowledge
- probabilistic modeling
- expert knowledge
- computer programming
- object oriented programming
- knowledge base
- high level
- active learning
- training data
- model selection
- knowledge acquisition
- object oriented
- probability distribution
- probabilistic model