期刊簡介預計審稿時間： 較慢,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.

機器學習是研究計算學習方法的國際論壇。該期刊發(fā)表的文章報告了應用于各種學習問題的廣泛學習方法的實質性成果，包括但不限于：

學習問題：分類、回歸、識別和預測；問題解決和規(guī)劃；推理和推論；數(shù)據(jù)挖掘；網(wǎng)絡挖掘；科學發(fā)現(xiàn)；信息檢索；自然語言處理；設計和診斷；視覺和語音感知；機器人和控制；組合優(yōu)化；游戲；各種工業(yè)、金融和科學應用。

學習方法：監(jiān)督和無監(jiān)督學習方法（包括學習決策和回歸樹、規(guī)則、聯(lián)結網(wǎng)絡、概率網(wǎng)絡和其他統(tǒng)計模型、歸納邏輯編程、基于案例的方法、集成方法、聚類等）；強化學習；基于進化的方法；基于解釋的學習；類比學習方法；自動知識獲??；從指令中學習；數(shù)據(jù)模式可視化；集成架構中的學習；多策略學習；多智能體學習。

《Machine Learning》(機器學習)編輯部通訊方式為SPRINGER, VAN GODEWIJCKSTRAAT 30, DORDRECHT, NETHERLANDS, 3311 GZ。如果您需要協(xié)助投稿或潤稿服務，您可以咨詢我們的客服老師。我們專注于期刊咨詢服務十年，熟悉發(fā)表政策，可為您提供一對一投稿指導，避免您在投稿時頻繁碰壁，節(jié)省您的寶貴時間，有效提升發(fā)表機率，確保SCI檢索（檢索不了全額退款）。我們視信譽為生命，多方面確保文章安全保密，在任何情況下都不會泄露您的個人信息或稿件內容。