Explainable AI: Machine Learning Interpretation in Blackcurrant Powders.

ABSTRACT: Recently, explainability in machine and deep learning has become an important area in the field of research as well as interest, both due to the increasing use of artificial intelligence (AI) methods and understanding of the decisions made by models. The explainability of artificial intelligence (XAI) is due to the increasing consciousness in, among other things, data mining, error elimination, and learning performance by various AI algorithms. Moreover, XAI will allow the decisions made by models in problems to be more transparent as well as effective. In this study, models from the 'glass box' group of Decision Tree, among others, and the 'black box' group of Random Forest, among others, were proposed to understand the identification of selected types of currant powders. The learning pro

SUBMITTER: Przybyl K 

PROVIDER: S-EPMC11124776 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature