{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T14:20:22Z","timestamp":1783434022832,"version":"3.54.6"},"reference-count":35,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.patcog.2026.114372","type":"journal-article","created":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T14:49:57Z","timestamp":1783090197000},"page":"114372","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PD","title":["Elastic net-based cost-sensitive broad learning system with F-measure maximization and density harmonization"],"prefix":"10.1016","volume":"180","author":[{"given":"Yanting","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiping","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yusha","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3747-1004","authenticated-orcid":false,"given":"Junwei","family":"Jin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyun","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C.L. Philip","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.patcog.2026.114372_b1","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111677","article-title":"Skew-probabilistic neural networks for learning from imbalanced data","volume":"165","author":"Naik","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114372_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.125422","article-title":"Synthetic oversampling with Mahalanobis distance and local information for highly imbalanced class-overlapped data","volume":"260","author":"Yan","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.patcog.2026.114372_b3","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.107126","article-title":"A meta-learning imbalanced classification framework via boundary enhancement strategy with Bayes imbalance impact index","volume":"185","author":"Li","year":"2025","journal-title":"Neural Netw."},{"issue":"1","key":"10.1016\/j.patcog.2026.114372_b4","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1109\/TNNLS.2017.2716952","article-title":"Broad learning system: An effective and efficient incremental learning system without the need for deep architecture","volume":"29","author":"Chen","year":"2017","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"5","key":"10.1016\/j.patcog.2026.114372_b5","doi-asserted-by":"crossref","first-page":"8331","DOI":"10.1109\/TNNLS.2024.3415621","article-title":"Adaptive memory broad learning system for unsupervised time series anomaly detection","volume":"36","author":"Zhong","year":"2025","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"6","key":"10.1016\/j.patcog.2026.114372_b6","doi-asserted-by":"crossref","first-page":"4029","DOI":"10.1109\/TCYB.2022.3181449","article-title":"Self-paced broad learning system","volume":"53","author":"Liu","year":"2023","journal-title":"IEEE Trans. Cybern."},{"issue":"4","key":"10.1016\/j.patcog.2026.114372_b7","doi-asserted-by":"crossref","first-page":"7196","DOI":"10.1109\/TNNLS.2024.3392583","article-title":"An incremental-self-training-guided semi-supervised broad learning system","volume":"36","author":"Guo","year":"2025","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.patcog.2026.114372_b8","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1016\/j.ins.2022.07.074","article-title":"Class-specific weighted broad learning system for imbalanced heartbeat classification","volume":"610","author":"Fan","year":"2022","journal-title":"Inf. Sci."},{"key":"10.1016\/j.patcog.2026.114372_b9","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.126824","article-title":"Class-specific weighted broad learning system-based domain adaptation for patient-specific ECG classification","volume":"273","author":"Fan","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.patcog.2026.114372_b10","doi-asserted-by":"crossref","DOI":"10.1016\/j.apenergy.2023.121914","article-title":"Multi-view broad learning system for electricity theft detection","volume":"352","author":"Yang","year":"2023","journal-title":"Appl. Energy"},{"key":"10.1016\/j.patcog.2026.114372_b11","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129427","article-title":"Coupling importance sampling neural network for imbalanced data classification with multi-level learning bias","volume":"623","author":"ao Huang","year":"2025","journal-title":"Neurocomputing"},{"issue":"1","key":"10.1016\/j.patcog.2026.114372_b12","doi-asserted-by":"crossref","DOI":"10.1155\/int\/6463038","article-title":"Software defect prediction based on fuzzy cost broad learning system","volume":"2025","author":"Cao","year":"2025","journal-title":"Int. J. Intell. Syst."},{"issue":"3","key":"10.1016\/j.patcog.2026.114372_b13","doi-asserted-by":"crossref","first-page":"1323","DOI":"10.1109\/TIP.2017.2781298","article-title":"Cost-sensitive feature selection by optimizing F-measures","volume":"27","author":"Liu","year":"2018","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.patcog.2026.114372_b14","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2019.107146","article-title":"F-measure curves: A tool to visualize classifier performance under imbalance","volume":"100","author":"Soleymani","year":"2020","journal-title":"Pattern Recognit."},{"issue":"5","key":"10.1016\/j.patcog.2026.114372_b15","doi-asserted-by":"crossref","first-page":"2767","DOI":"10.1109\/TCYB.2021.3126756","article-title":"Cost-sensitive hypergraph learning with F-measure optimization","volume":"53","author":"Wang","year":"2023","journal-title":"IEEE Trans. Cybern."},{"key":"10.1016\/j.patcog.2026.114372_b16","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.neucom.2021.01.033","article-title":"Relevant information undersampling to support imbalanced data classification","volume":"436","author":"Hoyos-Osorio","year":"2021","journal-title":"Neurocomputing"},{"key":"10.1016\/j.patcog.2026.114372_b17","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","article-title":"SMOTE: Synthetic minority over-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"J. Artificial Intelligence Res."},{"issue":"6","key":"10.1016\/j.patcog.2026.114372_b18","doi-asserted-by":"crossref","first-page":"923","DOI":"10.1002\/int.22230","article-title":"A self-adaptive synthetic over-sampling technique for imbalanced classification","volume":"35","author":"Gu","year":"2020","journal-title":"Int. J. Intell. Syst."},{"issue":"6","key":"10.1016\/j.patcog.2026.114372_b19","first-page":"5550","article-title":"A robust oversampling approach for class imbalance problem with small disjuncts","volume":"35","author":"Sun","year":"2023","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.patcog.2026.114372_b20","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.113803","article-title":"Minimum variance weighted broad cascade network structure for imbalanced classification","volume":"324","author":"Chen","year":"2025","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.patcog.2026.114372_b21","series-title":"CAAI International Conference on Artificial Intelligence","first-page":"462","article-title":"Weighted competitive-collaborative representation based classifier for imbalanced data classification","author":"Li","year":"2022"},{"issue":"6","key":"10.1016\/j.patcog.2026.114372_b22","doi-asserted-by":"crossref","first-page":"1949","DOI":"10.1109\/TFUZZ.2025.3543369","article-title":"Adaptive broad network with graph-fuzzy embedding for imbalanced noise data","volume":"33","author":"Chen","year":"2025","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"10.1016\/j.patcog.2026.114372_b23","series-title":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No. 04CH37541)","first-page":"1163","article-title":"AdaBoost. RT: A boosting algorithm for regression problems","volume":"vol. 2","author":"Solomatine","year":"2004"},{"key":"10.1016\/j.patcog.2026.114372_b24","series-title":"2020 IEEE 36th International Conference on Data Engineering","first-page":"841","article-title":"Self-paced ensemble for highly imbalanced massive data classification","author":"Liu","year":"2020"},{"key":"10.1016\/j.patcog.2026.114372_b25","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.130337","article-title":"Broad learning systems: An overview of recent advances, applications, challenges and future directions","volume":"641","author":"Chu","year":"2025","journal-title":"Neurocomputing"},{"issue":"11","key":"10.1016\/j.patcog.2026.114372_b26","doi-asserted-by":"crossref","first-page":"16076","DOI":"10.1109\/TNNLS.2023.3291793","article-title":"Flexible label-induced manifold broad learning system for multiclass recognition","volume":"35","author":"Jin","year":"2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.patcog.2026.114372_b27","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2025.108138","article-title":"A convolution and transformer-based method with effective stain normalization for breast cancer detection from whole slide images","volume":"110","author":"Goceri","year":"2025","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.patcog.2026.114372_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.126290","article-title":"An efficient network with CNN and transformer blocks for glioma grading and brain tumor classification from MRIs","volume":"268","author":"Goceri","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.patcog.2026.114372_b29","first-page":"1","article-title":"A hybrid attention-based deep learning model for segmentation of livers and liver tumors from CT scans","author":"Goceri","year":"2025","journal-title":"Multimedia Tools Appl."},{"key":"10.1016\/j.patcog.2026.114372_b30","doi-asserted-by":"crossref","first-page":"800","DOI":"10.1016\/j.ins.2021.06.008","article-title":"Discriminative group-sparsity constrained broad learning system for visual recognition","volume":"576","author":"Jin","year":"2021","journal-title":"Inform. Sci."},{"issue":"8","key":"10.1016\/j.patcog.2026.114372_b31","doi-asserted-by":"crossref","first-page":"5183","DOI":"10.1007\/s10994-023-06416-8","article-title":"GMMSampling: A new model-based, data difficulty-driven resampling method for multi-class imbalanced data","volume":"113","author":"Naglik","year":"2024","journal-title":"Mach. Learn."},{"issue":"5","key":"10.1016\/j.patcog.2026.114372_b32","doi-asserted-by":"crossref","first-page":"4334","DOI":"10.1007\/s10489-024-05393-2","article-title":"Hybrid density-based adaptive weighted collaborative representation for imbalanced learning","volume":"54","author":"Li","year":"2024","journal-title":"Appl. Intell."},{"key":"10.1016\/j.patcog.2026.114372_b33","doi-asserted-by":"crossref","unstructured":"Y. Li, Y. Wang, J. Jin, C.L.P. Chen, Feature fusion-based weighted broad learning system for imbalanced data, in: 2025 IEEE 8th Information Technology and Mechatronics Engineering Conference, ITOEC, vol. 8, 2025, pp. 708\u2013712.","DOI":"10.1109\/ITOEC63606.2025.10968350"},{"key":"10.1016\/j.patcog.2026.114372_b34","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2025.103842","article-title":"Efficient incremental learning for inverse matrix-free broad learning system","volume":"127","author":"Chen","year":"2026","journal-title":"Inf. Fusion"},{"issue":"5","key":"10.1016\/j.patcog.2026.114372_b35","doi-asserted-by":"crossref","first-page":"4064","DOI":"10.1109\/TCYB.2020.3015749","article-title":"Weighted generalized cross-validation-based regularization for broad learning system","volume":"52","author":"Gan","year":"2022","journal-title":"IEEE Trans. Cybern."}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326013373?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326013373?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T14:08:02Z","timestamp":1783433282000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320326013373"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":35,"alternative-id":["S0031320326013373"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2026.114372","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Elastic net-based cost-sensitive broad learning system with F-measure maximization and density harmonization","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2026.114372","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"114372"}}