Content Controlled Spectral Indices for Detection of Hydrothermal Alteration Minerals Based on Machine Learning and Lasso-Logistic Regression Analysis
This article introduced the quantity controlled spectral indices working at mineral contents higher than 5 wt.% for detection of sericite, chlorite, and pyrophyllite, which are the representative alteration minerals of phyllic, propylitic, and advanced argillic hydrothermal alterations. T...
Main Authors: | Kyuhun Shim, Jaehyung Yu, Lei Wang, Sangin Lee, Sang-Mo Koh, Bum Han Lee |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9489372/ |
Similar Items
-
The Major Driving Factors of Carbon Emissions in China and Their Relative Importance: An Application of the LASSO Model
by: Wai Yan Shum, et al.
Published: (2021-08-01) -
A novel gene expression test method of minimizing breast cancer risk in reduced cost and time by improving SVM-RFE gene selection method combined with LASSO
by: Gupta Madhuri, et al.
Published: (2020-12-01) -
Non-Destructive Measurement of Egg’s Haugh Unit by Vis-NIR with iPLS-Lasso Selection
by: Leiming Yuan, et al.
Published: (2023-01-01) -
Study on the Sparse Sub-block Microwave Imaging Based on Lasso(In English)
by: Xiang Yin, et al.
Published: (2013-09-01) -
Consensual Regression of Lasso-Sparse PLS models for Near-Infrared Spectra of Food
by: Lei-Ming Yuan, et al.
Published: (2022-10-01)