Zobrazeno 1 - 10
of 10 536
pro vyhledávání: '"oversampling"'
Publikováno v:
Jurnal Informatika, Vol 12, Iss 2, Pp 159-167 (2024)
Conducting sentiment research on the perception of the Indonesian people towards Shin Tae Yong's (STY) role as coach of the Indonesian National Football Team (PSSI) is crucial as it can assist PSSI in determining whether to extend STY's contract. Pri
Externí odkaz:
https://doaj.org/article/e457d1c9136d4d048f54f9a9e1a5d765
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract Credit scoring models are critical for financial institutions to assess borrower risk and maintain profitability. Although machine learning models have improved credit scoring accuracy, imbalanced class distributions remain a major challenge
Externí odkaz:
https://doaj.org/article/6f51d7d4f3b44c48a47e17c0fd3ddfc0
Autor:
Phan Anh Phong, Le Van Thanh
Publikováno v:
Tạp chí Khoa học, Vol 53, Iss 3A, Pp 5-15 (2024)
This paper proposes a method to enhance the effectiveness of classifying imbalanced data. The main contribution of the method is integrating the K-means clustering algorithm and the minority oversampling technique VCIR to generate synthetic samples t
Externí odkaz:
https://doaj.org/article/65f1e4fa5a394c75865bbff7cd519028
Autor:
Olivier Kashongwe, Tina Kabelitz, Christian Ammon, Lukas Minogue, Markus Doherr, Pablo Silva Boloña, Thomas Amon, Barbara Amon
Publikováno v:
AgriEngineering, Vol 6, Iss 3, Pp 3427-3442 (2024)
Missing data and class imbalance hinder the accurate prediction of rare events such as dairy mastitis. Resampling and imputation are employed to handle these problems. These methods are often used arbitrarily, despite their profound impact on predict
Externí odkaz:
https://doaj.org/article/1d9d667177fa4ee0a7e25f66a9810e4c
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-18 (2024)
Abstract Missing labels in multi-label datasets are a common problem, especially for minority classes, which are more likely to occur. This limitation hinders the performance of classifiers in identifying and extracting information from minority clas
Externí odkaz:
https://doaj.org/article/16c6e5a05b1945869f156bcfeebf84cc
Autor:
Hadi S.N., Chung R.H.
Publikováno v:
Russian Journal of Agricultural and Socio-Economic Sciences, Vol 151, Iss 7, Pp 91-106 (2024)
Although per capita beef consumption in Indonesia remains relatively low, the demand for beef has increased significantly over the past three decades. With domestic production unable to keep pace with this growing demand, the country has resorted to
Externí odkaz:
https://doaj.org/article/443ee928f5ed4935ab5f5a765aee5092
Autor:
S. Thanga Prasath, C. Navaneethan
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract Generally, a person’s life span depends on their food consumption because it may cause deadly diseases like colorectal cancer (CRC). In 2020, colorectal cancer accounted for one million fatalities globally, representing 10% of all cancer c
Externí odkaz:
https://doaj.org/article/427a983c3231403cbdc85d10c82644b0
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Fraud seriously threatens individual interests and social stability, so fraud detection has attracted much attention in recent years. In scenarios such as social media, fraudsters typically hide among numerous benign users, constituting only
Externí odkaz:
https://doaj.org/article/b62b4de5bef84c22982a7af294f89aef
Publikováno v:
Scientific Journal of Astana IT University, Pp 5-16 (2024)
The field of medicine is witnessing rapid development of AI, highlighting the importance of proper data processing. However, when working with medical data, there is a problem of class imbalance, where the amount of data about healthy patients signif
Externí odkaz:
https://doaj.org/article/db804aae1456473c8bf37dc87d158a96
Publikováno v:
International Journal of Applied Mathematics and Computer Science, Vol 34, Iss 2, Pp 291-307 (2024)
In practical applications of machine learning, the class distribution of the collected training set is usually imbalanced, i.e., there is a large difference among the sizes of different classes. The class imbalance problem often hinders the achievabl
Externí odkaz:
https://doaj.org/article/81bbe5599122433ea7e87cb212f0492f