A comprehensive tutorial on Data-Driven SIMCA: Theory and implementation in web

IF 2.3 4区化学 Q1 SOCIAL WORK

Journal of Chemometrics Pub Date : 2024-05-10 DOI:10.1002/cem.3556

Sergey Kucheryavskiy, Oxana Rodionova, Alexey Pomerantsev

引用次数: 0

Abstract

The aim of this paper is twofold. First, it serves as a comprehensive tutorial on Data-Driven Soft Independent Modelling of Class Analogy (SIMCA) (DD-SIMCA) method for one-class classification. It covers all practical aspects of developing, validation, and application of DD-SIMCA models, using a set of simple examples. Second, it introduces web application that implements the main DD-SIMCA functionality. This application is freely available for everyone and does not require registration or installation. All calculations run locally in a browser without sending any information on a server, hence removing any obstacles to the dissemination of the data and models.

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数据驱动 SIMCA 综合教程：网络理论与实施

本文有两个目的。首先，它是数据驱动的类类比软独立建模（SIMCA）（DD-SIMCA）方法用于单类分类的综合教程。它使用一组简单的示例，涵盖了开发、验证和应用 DD-SIMCA 模型的所有实际方面。其次，它介绍了实现 DD-SIMCA 主要功能的网络应用程序。该应用程序对所有人免费开放，无需注册或安装。所有计算均在本地浏览器中运行，无需向服务器发送任何信息，从而消除了数据和模型传播的任何障碍。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Chemometrics 化学-分析化学

CiteScore

5.20

自引率

8.30%

发文量

审稿时长

2 months

期刊介绍： The Journal of Chemometrics is devoted to the rapid publication of original scientific papers, reviews and short communications on fundamental and applied aspects of chemometrics. It also provides a forum for the exchange of information on meetings and other news relevant to the growing community of scientists who are interested in chemometrics and its applications. Short, critical review papers are a particularly important feature of the journal, in view of the multidisciplinary readership at which it is aimed.