Zobrazeno 1 - 10
of 6 823
pro vyhledávání: '"class imbalance"'
Autor:
Bayan Alabduallah, Mohammed Maray, Nuha Alruwais, Rana Alabdan, Abdulbasit A. Darem, Fouad Shoie Alallah, Raed Alsini, Ayman Yafoz
Publikováno v:
Alexandria Engineering Journal, Vol 106, Iss , Pp 654-663 (2024)
Cyberattack classification involves applying deep learning (DL) and machine learning (ML) models to categorize digital threats based on their features and behaviors. These models examine system logs, network traffic, or other associated data patterns
Externí odkaz:
https://doaj.org/article/d17c6852d17f49b6a0a4b75441c4c063
Autor:
Vanesa Gómez-Martínez, David Chushig-Muzo, Marit B. Veierød, Conceição Granja, Cristina Soguero-Ruiz
Publikováno v:
BioData Mining, Vol 17, Iss 1, Pp 1-30 (2024)
Abstract Background Cutaneous melanoma is the most aggressive form of skin cancer, responsible for most skin cancer-related deaths. Recent advances in artificial intelligence, jointly with the availability of public dermoscopy image datasets, have al
Externí odkaz:
https://doaj.org/article/50c8a3a4ed4c4155a53a138f8c5dda42
Publikováno v:
Big Data Mining and Analytics, Vol 7, Iss 3, Pp 920-941 (2024)
Financial statement fraud refers to malicious manipulations of financial data in listed companies’ annual statements. Traditional machine learning approaches focus on individual companies, overlooking the interactive relationships among companies t
Externí odkaz:
https://doaj.org/article/4abe6e7fdae4473ca58e85035de22299
Autor:
Shuangkai Han, Lin Liu
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 2034-2048 (2024)
Numerous research results demonstrated that understanding the subcellular localization of non-coding RNAs (ncRNAs) is pivotal in elucidating their roles and regulatory mechanisms in cells. Despite the existence of over ten computational models dedica
Externí odkaz:
https://doaj.org/article/dd6b7997c2784ad098b48d45c037aad4
Publikováno v:
Radiation Oncology, Vol 19, Iss 1, Pp 1-12 (2024)
Abstract Background The purpose of this study was to improve the deep learning (DL) model performance in predicting and classifying IMRT gamma passing rate (GPR) by using input features related to machine parameters and a class balancing technique. M
Externí odkaz:
https://doaj.org/article/0d1287c074d548e8980c8afd131da0d8
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Accurate prediction and grading of gliomas play a crucial role in evaluating brain tumor progression, assessing overall prognosis, and treatment planning. In addition to neuroimaging techniques, identifying molecular biomarkers that can guid
Externí odkaz:
https://doaj.org/article/31cd3cf6f9a14928b9f577145d06fc98
Publikováno v:
BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-14 (2024)
Abstract Background In binary classification for clinical studies, an imbalanced distribution of cases to classes and an extreme association level between the binary dependent variable and a subset of independent variables can create significant clas
Externí odkaz:
https://doaj.org/article/726428e025654a4da694db53c5d30959
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
Publikováno v:
International Journal of Applied Mathematics and Computer Science, Vol 34, Iss 2, Pp 323-334 (2024)
The imbalance and complexity of network traffic data are hot issues in the field of intrusion detection. To improve the detection rate of minority class attacks in network traffic, this paper presents a method for intrusion detection based on the rec
Externí odkaz:
https://doaj.org/article/8ac28a2b35d1447b97334f455804af52
Publikováno v:
Digital Communications and Networks, Vol 10, Iss 3, Pp 728-739 (2024)
The popularity of the Internet of Things (IoT) has enabled a large number of vulnerable devices to connect to the Internet, bringing huge security risks. As a network-level security authentication method, device fingerprint based on machine learning
Externí odkaz:
https://doaj.org/article/fa082e539c2b44fd9728b313ec88b5c6