المؤلفون: Salii, Jill

المساهمون: Paiva, Nuno, Veritati - Repositório Institucional da Universidade Católica Portuguesa

مصطلحات موضوعية: Synthetic data, Churn prediction, Imbalanced datasets, Telecommunication, SMOTENC, ADASYN, TVAE, CTGAN, Lift score, Data quality, Dados sintéticos, Previsão de churn, Conjuntos de dados desbalanceados, Indústria de telecomunicações, Qualidade dos dados, Domínio/Área Científica::Ciências Sociais::Economia e Gestão

وصف الملف: application/pdf

الاتاحة: http://hdl.handle.net/10400.14/45795

المؤلفون: Cheng-Hui Chen, Chen-Kun Tsung, Shyr-Shen Yu

المصدر: Applied Sciences; Volume 12; Issue 18; Pages: 9286

مصطلحات موضوعية: Mixed-Type Data, fault diagnosis, SmoteNC ctGAN, limited failure

جغرافية الموضوع: agris

وصف الملف: application/pdf

Relation: Computing and Artificial Intelligence; https://dx.doi.org/10.3390/app12189286

الاتاحة: https://doi.org/10.3390/app12189286

المؤلفون: Hasan, Md Abid, Rouf, Nirjhor Tahmidur, Hossain, Md Sajid, Latif, Lamia Binta, Tasnim, Anika, Grzegorzek, Marcin

مصطلحات موضوعية: Data Augmentation, Elbow Method, Flood Prediction, Random Forest, SMOTENC

Relation: International Conference on Tools with Artificial Intelligence 2023; #PLACEHOLDER_PARENT_METADATA_VALUE#; IEEE 35th International Conference on Tools with Artificial Intelligence, ICTAI 2023. Proceedings; https://publica.fraunhofer.de/handle/publica/467884

الاتاحة: https://publica.fraunhofer.de/handle/publica/467884
https://doi.org/10.1109/ICTAI59109.2023.00028

المؤلفون: Islam, Jobair

المساهمون: Åbo Akademi, Fakulteten för samhällsvetenskaper och ekonomi, Informationssystem

مصطلحات موضوعية: Advanced analytics, AI and ML, Backorder prediction, EDA, Imblanced dataset, Linear Regression, Parameter tuning, Predictive modeling, Random Forest, RUS, SMOTENC, XGBoost, supply chains, business operations, forecasts, optimisation, analysis, machine learning, algorithms, artificial intelligence, data, regression analysis, modelling (representation), leveranskedjor, företagsverksamhet, prognoser, optimering, maskininlärning, algoritmer, artificiell intelligens

وصف الملف: 143+V; true

Relation: https://www.doria.fi/handle/10024/188325; URN:NBN:fi-fe20231113146482

الاتاحة: https://www.doria.fi/handle/10024/188325

المؤلفون: Nana Chai, Baofeng Shi, Bin Meng, Yizhe Dong

المصدر: Chai, N, Shi, B, Meng, B & Dong, Y 2023, ' Default feature selection in credit risk modeling : Evidence from Chinese small enterprises ', SAGE Open, vol. 13, no. 2 . https://doi.org/10.1177/21582440231165224

مصطلحات موضوعية: AFCM-SMOTENC-APRIORI algorithm, association rule, General Arts and Humanities, General Social Sciences, imbalanced data, feature attributes, small enterprise

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d1d71be78b60c0f322dd68137288eac
https://doi.org/10.1177/21582440231165224