相关实验视频
Updated: Mar 8, 2026

Basics of Multivariate Analysis in Neuroimaging Data
Published on: July 24, 2010
关于多变量校准的旧建议:仍然有效,但并不总是遵循. 一个教程教程
1Departamento de Química Analítica, Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Suipacha 531, 2000, Rosario, Argentina; Instituto de Química Rosario (CONICET-UNR), 27 de Febrero 210 Bis, 2000, Rosario, Argentina.
更简单的局部最小方程 (PLS) 回归模型往往优于光谱数据分析的复杂深度学习方法. 节的方法产生了接近参考不确定性的准确预测,提高了多变量校准可靠性.
科学领域:
- 化学测量 化学测量 化学测量
- 频谱学是一种光谱学.
- 机器学习 机器学习
背景情况:
- 深度学习越来越多地用于多变量校准,经常忽视更简单的方法,如局部最小平方 (PLS) 回归.
- 缺乏对光谱预处理的必要性,预测错误的统计比较和参考技术不确定性影响的分析.
研究的目的:
- 为了比较深度学习和PLS回归用于光谱属性估计.
- 分析光谱预处理的必要性和适当的错误比较方法.
- 评估参考技术不确定性对模型性能的影响.
主要方法:
- 使用UV-Vis-NIR光谱对水果干物质含量估计的公开数据集进行分析.
- 全球和本地PLS模型与文学浅层和深度学习方法的比较.
- 评估与参考技术不确定性相关的预测错误.
主要成果:
- 与深度学习方法相比,本地PLS模型在简单性和准确性方面表现出更高的性能.
- 发现PLS模型的预测错误接近参考技术的不确定性.
- 该研究强调了在特定的多变量校准任务中对更简单模型的潜在偏好.
结论:
- 在多变量校准中采用节的概念可以提高稳定性和可靠性.
- 预测错误应与可靠校准参考值的不确定性保持一致.
- 像PLS这样的简单模型可以非常有效,并且应该与复杂的方法一起考虑.
更多相关视频
10:22Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
12:26Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
Published on: October 11, 2016
相关概念视频
Calibration Curves: Linear Least Squares
For data that follow a straight line, the standard method for fitting is the linear...
Calibration Curves: Correlation Coefficient
Instrument Calibration
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...
Multi-input and Multi-variable systems
In the absence of...
Glassware Calibration
Volumetric flasks: Volumetric flasks are designed to prepare aqueous solutions of precise volumes accurately with a calibration line on the neck. To calibrate a volumetric flask, it is important to fill it with distilled...
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...