Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Olayemi Joshua I"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract The linear regression is critical for data modelling, especially for scientists. Nevertheless, with the plenty of high-dimensional data, there are data with more explanatory variables than the number of observations. In such circumstances, t
Externí odkaz:
https://doaj.org/article/71c75ac92651442a9f9536362eb14e7f
Publikováno v:
Biometrics & Biostatistics International Journal. 8:39-42
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b03eeb626ea04a1723cd604c886be7a9
https://doi.org/10.15406/bbij.2019.08.00268
https://doi.org/10.15406/bbij.2019.08.00268
Publikováno v:
Journal of Nigerian Society of Physical Sciences, Vol 6, Iss 3 (2024)
In recent years, the significance of machine learning in agriculture has surged, particularly in post-harvest monitoring for sustainable aquaculture. Challenges like heterogeneity, irrelevant variables and multicollinearity hinder the implementation
Externí odkaz:
https://doaj.org/article/48d275aeb59e438ca50277e3d71adfa9
Autor:
Nwokike Chukwudike C, Olayemi Joshua I, Offorha Bright C, Eghwerido Joseph Thomas, Obubu Maxwell
Publikováno v:
Current Trends on Biostatistics and Biometrics. 1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::feab4a0f66d819b839688dba4cbcbeaa
https://doi.org/10.32474/ctbb.2019.01.000112
https://doi.org/10.32474/ctbb.2019.01.000112
Publikováno v:
Journal of Big Data, Vol 10, Iss 1, Pp 1-18 (2023)
Abstract Precision farming (PF) plays a crucial role in the field of agriculture to solve the challenges of food shortages in society. Heterogeneity, multicollinearity, and outliers are problems in PF because they can cause bias and lead to incorrect
Externí odkaz:
https://doaj.org/article/d42122a065e7468baac78329b438c08e
Publikováno v:
Journal of Nigerian Society of Physical Sciences, Vol 5, Iss 1 (2023)
A common problem in regression analysis using ordinary least squares (OLS) is the effect of outliers or contaminated data on the estimates of the parameters. A robust method that is not sensitive to outliers and can handle contaminated data is needed
Externí odkaz:
https://doaj.org/article/a348b0c2f5854aa0bf59921ce6221797
Publikováno v:
African Scientific Reports, Pp 115-115 (2023)
When multiple conflicting criteria are available and must be considered, Multi-Criteria Decision Making (MCDM), a subfield of operations research, aids the decision maker in addressing the problem. The use of MCDM, a valuable and effective technique
Externí odkaz:
https://doaj.org/article/7935cb220798424fba5d931661c0ddef