Feature Importance Ranking of Random Forest-Based End-to-End Learning Algorithm
Efficient land management and farming practices are critical to maintaining agricultural production, especially in Europe with limited arable land. It is very time consuming to rely on a manual field inspection of cultivated land to archive farm crops. But with the help of satellite monitoring data...
Main Authors: | Xiaoguang Yuan, Shiruo Liu, Wei Feng, Gabriel Dauphin |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-11-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/15/21/5203 |
Similar Items
-
Use and misuse of random forest variable importance metrics in medicine: demonstrations through incident stroke prediction
by: Meredith L. Wallace, et al.
Published: (2023-06-01) -
Application of Multi-Source Data for Mapping Plantation Based on Random Forest Algorithm in North China
by: Fan Wu, et al.
Published: (2022-10-01) -
Improving the Accuracy of Random Forest Classifier for Identifying Burned Areas in the Tangier-Tetouan-Al Hoceima Region Using Google Earth Engine
by: Houda Badda, et al.
Published: (2023-08-01) -
A New Noisy Random Forest Based Method for Feature Selection
by: Akhiat Yassine, et al.
Published: (2021-06-01) -
Graph Random Forest: A Graph Embedded Algorithm for Identifying Highly Connected Important Features
by: Leqi Tian, et al.
Published: (2023-07-01)