机器学习 SCIE

期刊简介预计审稿时间： 较慢,6-12周

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.

机器学习是研究计算学习方法的国际论坛。该期刊发表的文章报告了应用于各种学习问题的广泛学习方法的实质性成果，包括但不限于：

学习问题：分类、回归、识别和预测；问题解决和规划；推理和推论；数据挖掘；网络挖掘；科学发现；信息检索；自然语言处理；设计和诊断；视觉和语音感知；机器人和控制；组合优化；游戏；各种工业、金融和科学应用。

学习方法：监督和无监督学习方法（包括学习决策和回归树、规则、联结网络、概率网络和其他统计模型、归纳逻辑编程、基于案例的方法、集成方法、聚类等）；强化学习；基于进化的方法；基于解释的学习；类比学习方法；自动知识获取；从指令中学习；数据模式可视化；集成架构中的学习；多策略学习；多智能体学习。

《Machine Learning》(机器学习)编辑部通讯方式为SPRINGER, VAN GODEWIJCKSTRAAT 30, DORDRECHT, NETHERLANDS, 3311 GZ。如果您需要协助投稿或润稿服务，您可以咨询我们的客服老师。我们专注于期刊投稿服务十年，熟悉发表政策，可为您提供一对一投稿指导，避免您在投稿时频繁碰壁，节省您的宝贵时间，有效提升发表机率，确保SCI检索（检索不了全额退款）。我们视信誉为生命，多方面确保文章安全保密，在任何情况下都不会泄露您的个人信息或稿件内容。