AMIDST: a Java Toolbox for Scalable Probabilistic Machine Learning.
Andrés R. MasegosaAna M. MartínezDarío Ramos-LópezRafael CabañasAntonio SalmerónThomas D. NielsenHelge LangsethAnders L. MadsenPublished in: CoRR (2017)
Keyphrases
- machine learning
- machine learning methods
- lightweight
- probabilistic model
- bayesian networks
- machine learning algorithms
- machine learning approaches
- information extraction
- object oriented
- decision trees
- data mining
- artificial intelligence
- computer vision
- handling uncertainty
- highly scalable
- pattern recognition
- learning algorithm
- web applications
- feature selection
- database applications
- java programs
- learning tasks
- knowledge acquisition
- text classification
- source code
- inductive learning
- reinforcement learning
- supervised learning
- inductive logic programming
- posterior probability
- development environment
- software package
- open source
- web scale
- learning systems
- semi supervised learning
- generative model
- database
- programming language
- computational intelligence
- text mining
- natural language processing
- knowledge representation
- data model
- database systems
- databases