Details of Research Outputs

TitleData Mining
Creator
Date Issued2023
Source PublicationFlavoromics: An Integrated Approach to Flavor and Sensory Assessment
ISBN9781003816010;9781032210629
Author/Editor of Source PublicationLeo Nollet, Matteo Bordiga
Publication PlaceBoca Raton
PublisherCRC Press
Abstract

Flavoromics studies the chemical compound profiles of flavor (taste and aroma) using a data-driven methodology to correlate chemical compound profiles with the sensory properties of foods. Data mining is meant to extract meaningful knowledge from useful but non-evident information hidden within large datasets. It is performed to extract meaningful information from the samples and visualize the results. The learning of principles of common supervised and unsupervised multivariate statistical tools is important to select the right data mining methods. Therefore, this chapter introduces techniques for data mining and data analysis tasks, ranging from classification analysis, regression analysis, correlation analysis, and cluster analysis. For each topic, it covers basic concepts, task formulations, methodologies, and evaluation metrics.

Language英语English
DOI10.1201/9781003268758-7
URLView source
Scopus ID2-s2.0-85180909461
Citation statistics
Document TypeBook chapter
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/11596
CollectionFaculty of Science and Technology
Affiliation
Division of Science and Technology,Data Science Program,United International College (UIC),Zhuhai,Guangdong Province,China
First Author AffilicationBeijing Normal-Hong Kong Baptist University
Recommended Citation
GB/T 7714
Rui, Meng,Wenmeng, He. Data Mining. Boca Raton: CRC Press, 2023.
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