Zobrazeno 1 - 10
of 3 989
pro vyhledávání: '"Classification and regression"'
Publikováno v:
Journal of Modern Science, Vol 57, Iss 3, Pp 580-593 (2024)
The article presents a method for detecting and analysing disease entities associated with lung diseases. The results are related to work on the design of a medical diagnostic system based on impedance tomography. One of the key features of the solut
Externí odkaz:
https://doaj.org/article/6068e75766df4a56a08df833237b78cb
Publikováno v:
Jurnal Lebesgue, Vol 5, Iss 2, Pp 964-973 (2024)
A classification model is needed to predict data into the right class according to the pattern of previous data. Binary Logistic Regression can be used in building classification models, even though the independent variables are categorical scale dat
Externí odkaz:
https://doaj.org/article/6da2d8e8c0864a108533ec6b74417b1c
Autor:
Ziyang Zhang, Deliang Lv, Yueyue You, Zhiguang Zhao, Wei Hu, Fengzhu Xie, Yali Lin, Wei Xie, Xiaobing Wu
Publikováno v:
Journal of Family and Community Medicine, Vol 31, Iss 3, Pp 197-205 (2024)
BACKGROUND: Diabetic retinopathy (DR) is one of the serious complications of diabetes mellitus (DM). Many studies have identified the risk factors associated with DR, but there is not much evidence on the importance of these factors for DR. This stud
Externí odkaz:
https://doaj.org/article/cb638bf4e17045799144d919a73c327d
Autor:
Haoting Tian, Yan Zhang, Xiaohui Yang, Huan Zhang, Dengfeng Wang, Pengbao Wu, Aijing Yin, Chao Gao
Publikováno v:
Ecotoxicology and Environmental Safety, Vol 285, Iss , Pp 117125- (2024)
The entry of Cd into soil-rice systems is a growing concern as it can pose potential risks to public health. To derive regional soil Cd threshold, a total of 333 paired soil and rice samples was collected in Anhui Province, Eastern China. The results
Externí odkaz:
https://doaj.org/article/f20e30a00ddb4e5eb0da54db6729d6eb
Publikováno v:
Intensive Care Research, Vol 4, Iss 2, Pp 116-128 (2024)
Abstract Background Machine learning (ML) can be promising for stratifying patients into homogeneous groups and assessing mortality based on score combination. Using ML, we compared mortality prediction performance for clustered and non-clustered mod
Externí odkaz:
https://doaj.org/article/4993a22ae25a4284950bf61b9b4203a5
Publikováno v:
Journal of Universal Computer Science, Vol 30, Iss 4, Pp 531-560 (2024)
The use of machine learning in real estate is quite new. When the working area is large, the factors affecting the price may vary according to the geographical regions and socioeconomic factors. It is thought that the price prediction performance of
Externí odkaz:
https://doaj.org/article/f0da5beba93b487aadbe6d65a4fa7f42
Publikováno v:
Crop and Environment, Vol 3, Iss 1, Pp 25-32 (2024)
Maize is the staple food crop in Bhutan, which has not achieved national food self-sufficiency. On-farm assessment of yield variability would provide insights into the priorities for Bhutan's maize development program. Here, we conducted three studie
Externí odkaz:
https://doaj.org/article/9285a27e76dc40e3a09040dcc62fe5ea
Autor:
Kazi Tahsin Huda, Ahmed Al-Kaisy
Publikováno v:
Future Transportation, Vol 4, Iss 1, Pp 257-269 (2024)
This paper proposes a new method for network screening on rural low-volume roads. These roads are important as they provide critical access to agricultural land and tourist attractions. Most low-volume roads belong to the lowest functional class (loc
Externí odkaz:
https://doaj.org/article/cef42656634d4048a543162a4cc2c34c
Publikováno v:
International Journal of Electrical Power & Energy Systems, Vol 158, Iss , Pp 109677- (2024)
This paper presents a method for the control design of five-level DCC converters based on mixed-integer optimization and machine learning. The resulting controller is computationally simple and can be easily implemented on low-resource control hardwa
Externí odkaz:
https://doaj.org/article/805b169357f74a47ad236f042d31f12c
Publikováno v:
Agricultural Water Management, Vol 299, Iss , Pp 108869- (2024)
In this study, we investigate the feasibility of using the Classification and Regression Tree (CART) algorithm to estimate soil water content (SWC) using commonly available meteorological parameters. We trained and validated CART models using data co
Externí odkaz:
https://doaj.org/article/a65c771515754dafb687368a69832d26