Zobrazeno 1 - 10
of 1 230
pro vyhledávání: '"under-sampling"'
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-25 (2024)
Abstract Class imbalance is one of many problems of customer churn datasets. One of the common problems is class overlap, where the data have a similar instance between classes. The prediction task of customer churn becomes more challenging when ther
Externí odkaz:
https://doaj.org/article/5670f06b48934da7b2b72560b02fba5c
Publikováno v:
International Soil and Water Conservation Research, Vol 12, Iss 3, Pp 548-564 (2024)
Check dams have been widely constructed in the Chinese Loess Plateau and has played an important role in controlling soil loss during last 70 years. However, the large-scale and automatic mapping of the check dams and the resulting silted fields are
Externí odkaz:
https://doaj.org/article/a665bfacaf3641d59b626eaa9d0382b2
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract This paper presents a new methodology for addressing imbalanced class data for failure prediction in Water Distribution Networks (WDNs). The proposed methodology relies on existing approaches including under-sampling, over-sampling, and clas
Externí odkaz:
https://doaj.org/article/3a7a64bb976d4347ac86ef53bc2b0fec
Publikováno v:
Zhejiang dianli, Vol 43, Iss 3, Pp 65-74 (2024)
In response to the challenge of sample data imbalance in fault diagnosis methods for photovoltaic power plants based on machine learning, the paper proposes a fault diagnosis method leveraging an enhanced BP-Bagging algorithm. Firstly, a mapping
Externí odkaz:
https://doaj.org/article/2848afd732c34faebc3580968fb67563
Autor:
Ajay Kumar
Publikováno v:
Journal of Communications Software and Systems, Vol 20, Iss 1, Pp 69-75 (2024)
A significant research challenge in data mining and machine learning is class imbalance classification since the majority of real-world datasets are imbalanced. When the dataset is highly unbalanced, the majority of available classification technique
Externí odkaz:
https://doaj.org/article/326c30c0228343bc87e314514f40381f
Autor:
Vibha Pratap, Amit Prakash Singh
Publikováno v:
Journal of Applied Science and Engineering, Vol 27, Iss 4, Pp 2319-2329 (2024)
The class imbalance is an important topic of research as imbalance exists in many applications where the presence of one type of sample is significantly greater than that of another type. To overcome binary class imbalance problems, a hybrid under-sa
Externí odkaz:
https://doaj.org/article/46db5fd3b1104763b30420af44f36a11
Publikováno v:
Healthcare Analytics, Vol 6, Iss , Pp 100359- (2024)
The primary goal of this research is to examine the impact of balancing data on the prediction quality and inference in multilevel logistic regression models. Logistic regression is a valuable approach for modeling binary outcomes expected in health
Externí odkaz:
https://doaj.org/article/563edf3a111c42758ab43b65d11e867d
Publikováno v:
Journal of Big Data, Vol 10, Iss 1, Pp 1-36 (2023)
Abstract Under-sampling is a technique to overcome imbalanced class problem, however, selecting the instances to be dropped and measuring their informativeness is an important concern. This paper tries to bring up a new point of view in this regard a
Externí odkaz:
https://doaj.org/article/85c2fedeec624ed499505d9f65c1a53a
Publikováno v:
Information, Vol 15, Iss 8, p 478 (2024)
In the cybersecurity industry, where legitimate transactions far outnumber fraudulent ones, detecting fraud is of paramount significance. In order to evaluate the accuracy of detecting fraudulent transactions in imbalanced real datasets, this study c
Externí odkaz:
https://doaj.org/article/2f6526ab7a6443a98dcea95d2e70a2f4
Publikováno v:
Heliyon, Vol 10, Iss 3, Pp e25466- (2024)
With the advancement of e-commerce and modern technological development, credit cards are widely used for both online and offline purchases, which has increased the number of daily fraudulent transactions. Many organizations and financial institution
Externí odkaz:
https://doaj.org/article/1d94cee125dc440ea1042844f413a9b9