题名 | Data Mining |
作者 | |
出版日期 | 2023 |
来源专著 | Flavoromics: An Integrated Approach to Flavor and Sensory Assessment |
ISBN | 9781003816010;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 |
DOI | 10.1201/9781003268758-7 |
URL | 查看来源 |
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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