科研成果详情

题名Data Mining
作者
出版日期2023
来源专著Flavoromics: An Integrated Approach to Flavor and Sensory Assessment
ISBN9781003816010;9781032210629
源著作者/编者Leo Nollet, Matteo Bordiga
出版地Boca Raton
出版者CRC Press
摘要

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.

语种英语English
DOI10.1201/9781003268758-7
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Scopus入藏号2-s2.0-85180909461
引用统计
文献类型著作章节
条目标识符https://repository.uic.edu.cn/handle/39GCC9TT/11596
专题理工科技学院
作者单位
Division of Science and Technology,Data Science Program,United International College (UIC),Zhuhai,Guangdong Province,China
第一作者单位北师香港浸会大学
推荐引用方式
GB/T 7714
Rui, Meng,Wenmeng, He. Data Mining. Boca Raton: CRC Press, 2023.
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