MADGUI：多应用程序设计图形用户界面，用于贝叶斯优化辅助的主动学习

IF 3.7 2区化学 Q2 AUTOMATION & CONTROL SYSTEMS

Chemometrics and Intelligent Laboratory Systems Pub Date : 2025-01-21 DOI:10.1016/j.chemolab.2025.105323

Christophe Bajan, Guillaume Lambard

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引用次数: 0

摘要

我们提出了MADGUI，多应用程序设计图形用户界面（GUI），使用贝叶斯优化和预测模型进行数据分析和优化过程或组成。它的优势在于它的用户友好设计，不需要编程知识。它是使用Python中的Streamlit库构建的，分为三个部分，允许用户选择各种参数并填充csv/xlsx文件，而无需任何编码。总体而言，MADGUI被设计为具有主动机器学习的最佳实验设计平台，它加速了最佳解决方案的发现，并为没有编码，机器学习或优化经验的用户提供了直观的GUI。

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MADGUI: Multi-Application Design Graphical User Interface for active learning assisted by Bayesian optimization

We present MADGUI, Multi-Application Design Graphical User Interface (GUI) using Bayesian Optimization and prediction model for data analysis and optimize process or composition. Its strength is its user-friendly design, which requires no programming knowledge. It is built using the Streamlit library in Python and is divided into three parts, allowing users to select various parameters and fill csv/xlsx files without any coding required. Overall, MADGUI is designed as an optimal experiment design platform with active machine learning, which accelerates the discovery of optimal solutions and provides an intuitive GUI for users with no experience in coding, machine learning, or optimization.

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来源期刊

Chemometrics and Intelligent Laboratory Systems 工程技术-分析化学

CiteScore

7.50

自引率

7.70%

发文量

169

审稿时长

3.4 months

期刊介绍： Chemometrics and Intelligent Laboratory Systems publishes original research papers, short communications, reviews, tutorials and Original Software Publications reporting on development of novel statistical, mathematical, or computer techniques in Chemistry and related disciplines. Chemometrics is the chemical discipline that uses mathematical and statistical methods to design or select optimal procedures and experiments, and to provide maximum chemical information by analysing chemical data. The journal deals with the following topics: 1) Development of new statistical, mathematical and chemometrical methods for Chemistry and related fields (Environmental Chemistry, Biochemistry, Toxicology, System Biology, -Omics, etc.) 2) Novel applications of chemometrics to all branches of Chemistry and related fields (typical domains of interest are: process data analysis, experimental design, data mining, signal processing, supervised modelling, decision making, robust statistics, mixture analysis, multivariate calibration etc.) Routine applications of established chemometrical techniques will not be considered. 3) Development of new software that provides novel tools or truly advances the use of chemometrical methods. 4) Well characterized data sets to test performance for the new methods and software. The journal complies with International Committee of Medical Journal Editors'' Uniform requirements for manuscripts.