特征(语言学)
基础(线性代数)
计算机科学
人工智能
模式识别(心理学)
数学
几何学
语言学
哲学
作者
Fucheng Zhao,Xiaosong Han,Yikun Zhang,Peiyu Niu,Jun Cheng,Yi Wan
标识
DOI:10.1109/bigcom53800.2021.00029
摘要
In TCM (Traditional Chinese Medicine) theory, the cold-and-hot property of food is considered as an important information to guide people's daily diet and keep them healthy. But the classification of this property mostly relies on experience from medical books, which lacks corresponding molecular chemistry basis and makes differentiation very difficult for ordinary people. To solve above question, in this paper, we collected 500 kinds of food and their nutrients, used ANOVA algorithm for feature selection to find out the nutrient feature that have a greater correlation with the cold and hot properties of food, and then used LightGBM algorithm to classify the processed data set. Finally, we constructed a reliable and accurate classification model and found the related nutritional elements are Tyrosine, Arginine, Thiamine, Vitamin B6 and Selenium.
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