The research of regression model in machine learning field

• Published in: MATEC web of conferences 2018-01, Vol.176, p.1033
• Main Authors: Rong, Shen, Bao-wen, Zhang
• Format: Article
• Language: English
• Subjects: Cleaning; Data mining; Dependent variables; Independent variables; Machine learning; Mathematical analysis; Regression analysis; Regression models; Weather forecasting
• ISSN: 2261-236X; 2274-7214; 2261-236X
• DOI: 10.1051/matecconf/201817601033

The paper herein will analyze the sale of iced products affected by variation of temperature. Firstly, we will collect the data of the forecast temperature last year and the sale of iced products and then conduct data compilation and cleansing. Finally, we will set up the mathematical regression analysis model based on the cleansed data by means of data mining theory. Regression analysis refers to the method of studying the relationship between independent variable and dependent variable. Linear regression model that corresponds to the practical situation is proposed in the paper, which is to set up simple linear regression model based on practical problem and then to implement the following with the help of the latest and most popular Python3.6. Python3.6 boasts the features of pure object-oriented, platform independence and concise and elegant language. So we will call the corresponding library function to predict the sale of iced products according to the variation of temperature, which will provide the foundation for the company to adjust its production each month, or even each week and each day. As a result, the situation of overproduction can be avoided. Moreover, the other situation as the profit will be affected by the lack of production since the rise of temperature will also be avoided. So the regression model also has reference value for the other fields of marketing.