GetPortalImpactFactorByIdResp(projectId=1, id=63464621, cover=https://img.medsci.cn/images/journal/cover/2021/cQX_202109271315579340.jpg, fullname=MACHINE LEARNING, abbr=MACH LEARN, pyear=1986, frequence=Monthly, articleNumbers=4242, citedSelf2015=3.1, acceptanceRate=null, submissionToAcceptance=null, averageReviewTime=暂无数据, reviewFee=null, pageFee=null, publishedRatio=2023年中国人文章占该期刊总数量13.66% (2022年为17.69%), issn=0885-6125, greenSci=https://www.greensci.net/search?kw=0885-6125, scijournal=https://www.scijournal.org/impact-factor-of-MACH-LEARN.shtml, medsciHotlightString=null, medsciHotlightRealtime=2.149, medsciHotlight=2.511, medsciHotlight5year=3.26568, citescore=11.0, hIndex=152, impactFactor=7.5, orgnization=Springer Netherlands, orgnizationUrl=http://springerlink.com, country=Netherlands, countryCn=荷兰, isOa=0, isOaString=否, sciScie=Science Citation Index|Science Citation Index Expanded|Current Contents - Engineering, Computing &amp; Technology, bigclassCas=工程技术 3区, smallclassCas=工程技术 3 区, website=https://link.springer.com/journal/10994, websiteHits=4114, guideForAuthor=null, guideForAuthorHits=2, submitWebsite=https://www.editorialmanager.com/mach/, submitWebsiteHits=1760, content=Machine Learning is an international forum for research on computational approaches to learning. The journal publishes articles reporting substantive research results on a wide range of learning methods applied to a variety of task domains including but not limited to: Methods: Inductive learning methods; Explanation-based learning; Genetic algorithms; Analogy and case-based methods; Connectionist techniques; Automated knowledge acquisition; Learning from instruction. Task Domains: Classification and recognition; Problem solving and planning; Reasoning and inference; Natural language processing; Design and diagnosis; Vision and speech perception; Robotics and motor control. The ideal paper will make a theoretical contribution supported by a computer implementation. In addition to carefully describing the learning component it should also discuss knowledge representation and performance assumptions. The article should carefully evaluate the approach through empirical studies theoretical analysis or comparison to psychological phenomena and should discuss its relation to other work in machine learning. Variations from this prototype such as critical reviews of existing work will be considered provided they make a clear contribution to the field., totalCites=31820, brief=MACH LEARN杂志工程技术行业，“<strong><a target="_blank" href="/sci/index.do?smallclass=计算机：人工智能" >计算机：人工智能</a></strong>”子行业的优秀级杂志, articleType=该刊全部是论著，可能不接收综述类等文章, medsciHeat=<span style="color: #990000;">暗红</span>, medsciComment=MACH LEARN杂志级别还可以，但是相对来说，比较冷门，关注人数偏少，有些可能是国内不太熟悉，但该杂志在国际仍然有相当知晓度的。因为缺少中国人投稿，稿源可能未必丰富，发表有可能有很大的机会哦。, medsciExplanation=MedSci期刊指数是根据中国科研工作者（含医学临床，基础，生物，化学等学科）对SCI杂志的认知度，熟悉程度，以及投稿的量等众多指标综合评定而成。当然，具体的，您还可以结合“<a href='https://www.medsci.cn/sci/submit.do?id=63464621'>投稿经验系统</a>”，进行综合判断，这更是大家的实战经验，值得分享和参考。<br> 注意，上述MedSci期刊指数采用MedSci专利技术，由计算机系统自动计算，并给出建议，存在不准确的可能，仅供您投稿选择杂志时参考。, tags=null, citeScoreList=[GetImpactFactorCiteScoreListResponse(year=2017, citescore=2.52), GetImpactFactorCiteScoreListResponse(year=2018, citescore=2.78), GetImpactFactorCiteScoreListResponse(year=2019, citescore=5.0), GetImpactFactorCiteScoreListResponse(year=2020, citescore=6.1), GetImpactFactorCiteScoreListResponse(year=2023, citescore=11.0)], medsciIndexList=[GetImpactFactorMedsciIndexListResponse(year=2022, medsciHotlight=2.643), GetImpactFactorMedsciIndexListResponse(year=2023, medsciHotlight=2.262), GetImpactFactorMedsciIndexListResponse(year=2024, medsciHotlight=2.466), GetImpactFactorMedsciIndexListResponse(year=2025, medsciHotlight=2.106), GetImpactFactorMedsciIndexListResponse(year=2026, medsciHotlight=2.149)], citeScoreGradeList=[GetImpactFactorCiteScoreGradeResponse(smallClass=Computer Science - Software , rank=102/360), GetImpactFactorCiteScoreGradeResponse(smallClass=Computer Science - Artificial Intelligence , rank=56/189)], totalJcrAreaList=[GetImpactFactorCiteScoreGradeResponse(smallClass=COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE, rank=Q2)], pmcUrl=https://www.ncbi.nlm.nih.gov/nlmcatalog?term=0885-6125[ISSN], pubmedUrl=https://www.ncbi.nlm.nih.gov/pubmed?cmd=search&term=MACHINE LEARNING[ta], article_number=147, article_number_cn=26, earlyWarning=null, linkOutUrl=null, isJournalMember=false, unscrambleContent=null, dayViewCount=false, endexampletyle=暂无数据)