{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T20:18:26Z","timestamp":1740169106326,"version":"3.37.3"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772090"],"award-info":[{"award-number":["61772090"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["CSC 201708060147"],"award-info":[{"award-number":["CSC 201708060147"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2925350","type":"journal-article","created":{"date-parts":[[2019,6,27]],"date-time":"2019-06-27T20:03:36Z","timestamp":1561665816000},"page":"85241-85252","source":"Crossref","is-referenced-by-count":13,"title":["Evaluation of Machine Learning Approaches for Android Energy Bugs Detection With Revision Commits"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2145-0559","authenticated-orcid":false,"given":"Chenyang","family":"Zhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhengwei","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunxin","family":"Xie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2750-6891","authenticated-orcid":false,"given":"Wei","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guiling","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1013203451"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(01)00065-2"},{"key":"ref33","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1007\/978-0-387-21579-2_9","article-title":"The boosting approach to machine learning: An overview","volume":"171","author":"schapire","year":"2003","journal-title":"Nonlinear Estimation Classification"},{"key":"ref32","first-page":"1471","article-title":"Training and testing low-degree polynomial data mappings via linear SVM","volume":"11","author":"chang","year":"2010","journal-title":"J Mach Learn Res"},{"key":"ref31","first-page":"155","article-title":"Support vector regression machines","author":"drucker","year":"1997","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/BF00994018"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45014-9_1"},{"key":"ref35","first-page":"107","article-title":"Improving regressors using boosting techniques","volume":"97","author":"drucker","year":"1997","journal-title":"Proc ICML"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1006\/jcss.1997.1504"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/2597073.2597097"},{"key":"ref40","first-page":"63","article-title":"Gaussian processes in machine learning","author":"rasmussen","year":"2003","journal-title":"Machine Learning Summer School"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1145\/2840723","article-title":"Modeling, profiling, and debugging the energy consumption of mobile devices","volume":"48","author":"hoque","year":"2016","journal-title":"ACM Comput Surv"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICSME.2017.79"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.5755\/j01.eee.19.6.4577"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE.2013.6606555"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.scico.2017.05.002"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s10664-018-9640-7"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/2307636.2307661"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/2635868.2635871"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.2478\/mms-2013-0036"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729586"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/MS.2015.83"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68690-5_12"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2017.07.005"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/PL00011414"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/1966445.1966460"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/505282.505283"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2016.2601299"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/GreenCom-iThings-CPSCom.2013.45"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/2901739.2901763"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSME.2014.34"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/2568225.2568321"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/SANER.2016.77"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/2593743.2593750"},{"key":"ref42","first-page":"1137","article-title":"A study of cross-validation and bootstrap for accuracy estimation and model selection","author":"kohavi","year":"1995","journal-title":"Proc 14th Int Joint Conf Artif Intell"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/MOBILESoft.2017.21"},{"journal-title":"Time","year":"2019","key":"ref41"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/2897073.2897086"},{"key":"ref44","article-title":"Hyperparameter search in machine learning","author":"claesen","year":"2015","journal-title":"arXiv 1502 02127"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/BF00993504"},{"key":"ref43","first-page":"172","article-title":"Principles and procedures of statistics, with special reference to the biological sciences","volume":"52","author":"carpenter","year":"1960","journal-title":"The Eugenics Review"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2018.11.013"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08747004.pdf?arnumber=8747004","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,10]],"date-time":"2021-08-10T19:40:03Z","timestamp":1628624403000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8747004\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":44,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2925350","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2019]]}}}