Machine Learning is an international forum for research on computational approaches to learning. The journal publishes articles reporting substantive results on a wide range of learning methods applied to a variety of learning problems| including but not limited to: Learning Problems: Classification| regression| recognition| and prediction; Problem solving and planning; Reasoning and inference; Data mining; Web mining; Scientific discovery; Information retrieval; Natural language processing; Design and diagnosis; Vision and speech perception; Robotics and control; Combinatorial optimization; Game playing; Industrial| financial| and scientific applications of all kinds. Learning Methods: Supervised and unsupervised learning methods (including learning decision and regression trees| rules| connectionist networks| probabilistic networks and other statistical models| inductive logic programming| case-based methods| ensemble methods| clustering| etc.); Reinforcement learning; Evolution-based methods; Explanation-based learning; Analogical learning methods; Automated knowledge acquisition; Learning from instruction; Visualization of patterns in data; Learning in integrated architectures; Multistrategy learning; Multi-agent learning.
数据整理自公开网络的投稿反馈，仅供参考。
