{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T05:28:15Z","timestamp":1730266095513,"version":"3.28.0"},"reference-count":30,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7]]},"DOI":"10.1109\/ijcnn.2018.8489290","type":"proceedings-article","created":{"date-parts":[[2018,10,19]],"date-time":"2018-10-19T22:25:09Z","timestamp":1539987909000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["An Experimental Perspective on Sampling Methods for Imbalanced Learning From Financial Databases"],"prefix":"10.1109","author":[{"given":"Luis Eduardo Boiko","family":"Ferreira","sequence":"first","affiliation":[]},{"given":"Jean Paul","family":"Barddal","sequence":"additional","affiliation":[]},{"given":"Fabricio","family":"Enembreck","sequence":"additional","affiliation":[]},{"given":"Heitor Murilo","family":"Gomes","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref30","first-page":"2825","article-title":"Scikit-learn: Machine learning in python","volume":"12","year":"2011","journal-title":"et al"},{"year":"2017","key":"ref10","article-title":"Product recommendation systems based on hybrid approach technology"},{"year":"2017","key":"ref11","article-title":"A statistical and machine learning model to detect money laundering: an application,” 2017. ´learning for financial fraud detection in the accounts of companies investigated for money laundering"},{"journal-title":"et al","article-title":"Using machine learning for financial fraud detection in the accounts of companies investigated for money laundering","year":"2017","key":"ref12"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.04.006"},{"year":"2007","key":"ref14","article-title":"Supervised machine learning: A review of classification techniques"},{"journal-title":"Decision Support Systems","article-title":"A data mining based system for credit-card fraud detection in e-tail","year":"2017","key":"ref15"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2014.2336263"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.08.030"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2017.10.017"},{"key":"ref19","first-page":"215","article-title":"The regression analysis of binary sequences","year":"1958","journal-title":"Journal of the Royal Statistical Society Series B (Methodological)"},{"key":"ref28","first-page":"1322","article-title":"Adasyn: Adaptive synthetic sampling approach for imbalanced learning","year":"2008","journal-title":"Neural Networks 2008 IJCNN 2008 (IEEE World Congress on Computational Intelligence) IEEE International Joint Conference on"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.02.001"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/1007730.1007735"},{"year":"2014","key":"ref3","article-title":"Peer lending risk predictor"},{"year":"2017","key":"ref6","article-title":"Machine learning for fraud detection"},{"year":"2013","key":"ref29","article-title":"UCI machine learning repository"},{"key":"ref5","first-page":"193","article-title":"Credit risk analysis in peer-to-peer lending system","year":"2016","journal-title":"IEEE International Conference on Knowledge Engineering and Applications (ICKEA)"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2017.11.001"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"937","DOI":"10.1007\/s13198-016-0551-y","article-title":"A survey of machine-learning and nature-inspired based credit card fraud detection techniques","volume":"8","year":"2017","journal-title":"International Journal of System Assurance Engineering and Management"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2006.04.018"},{"year":"2017","key":"ref9","article-title":"A review on the page recommendation model using machine learning approaches"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.03.049"},{"year":"1968","key":"ref20","article-title":"Naive bayes classifier"},{"key":"ref22","first-page":"133","article-title":"Logistic regression bias correction for large scale data with rare events","year":"2013","journal-title":"Part II of the Proceedings of the 9th International Conference on Advanced Data Mining and Applications -Volume 8347"},{"journal-title":"Decision trees for decision making","year":"1964","key":"ref21"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/BF00153759"},{"key":"ref23","first-page":"31","article-title":"A survey of predictive modeling on imbalanced domains","volume":"49","year":"2016","journal-title":"ACM Comput Surv"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s13748-014-0045-6"}],"event":{"name":"2018 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2018,7,8]]},"location":"Rio de Janeiro","end":{"date-parts":[[2018,7,13]]}},"container-title":["2018 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8465565\/8488986\/08489290.pdf?arnumber=8489290","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,24]],"date-time":"2020-08-24T05:56:19Z","timestamp":1598248579000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8489290\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/ijcnn.2018.8489290","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}