Ensemble data mining methods for assessing soil fertility
The application of ensemble data mining methods in assessing soil fertility and the use of methods such as random forest, gradient boosting and bagging to determine the level of soil fertility are examined in the article. Ensemble methods combine multiple machine learning models to improve the accur...
Main Authors: | Ziyadullaev Davron, Muhamediyeva Dilnoz, Khujamkulova Khosiyat, Abdurakhimov Doniyor, Maksumkhanova Azizahon, Ziyodullaeva Gulchiroy |
---|---|
Format: | Article |
Language: | English |
Published: |
EDP Sciences
2024-01-01
|
Series: | E3S Web of Conferences |
Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/24/e3sconf_aees2024_02013.pdf |
Similar Items
-
Solving diabetes diagnosis problems using machine learning
by: Olimboyeva Donaxon, et al.
Published: (2024-01-01) -
Application of the neuro-fuzzy approach to solving problems of soil phases evaluation
by: Ziyadullaev Davron, et al.
Published: (2023-01-01) -
Data mining for assessing soil fertility
by: Inoyatova Manzura, et al.
Published: (2024-01-01) -
Mathematical modeling and numerical calculation of an epidemic with medical vaccination in account
by: Ziyadullaev Davron, et al.
Published: (2023-01-01) -
Application of ensemble machine learning methods for diabetes diagnosis
by: Ziyadullaev Davron, et al.
Published: (2024-01-01)