A comprehensive tutorial on Data‐Driven SIMCA: Theory and implementation in web
Sergey Kucheryavskiy, Oxana Ye. Rodionova, Alexey L. Pomerantsev
Abstract
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.
Topics & Concepts
Computer scienceInformation retrievalData miningFault Detection and Control SystemsSpectroscopy and Chemometric AnalysesAdvanced Data Processing Techniques