Python教学实验环境下回归预测模型的实践  

The Practice of Regression Prediction Model under Python Teaching Experiment Environment

作　　者：沈荣 张保文 SHEN Rong;ZHANG Bao-wen(School of Information Engineering,Ningxia University,Yinchuan 750021,China;School of Mathematics and Statistics,Ningxia University,Yinchuan 750021,China)

机构地区：[1]宁夏大学信息工程学院,宁夏银川750021 [2]宁夏大学数学统计学院,宁夏银川750021

出　　处：《电脑知识与技术》2019年第4期254-256,258,共4页Computer Knowledge and Technology

基　　金：宁夏高等学校科学研究项目(编号:NGY2017032)

摘　　要：通过建立多元线性回归分析模型,采用数据挖掘理论中的数据分析方法对蛋糕店月营业额的特征因素进行提取,确定距离车站最近距离和店铺面积作为特征因素,从而对蛋糕房月营业额进行预测。利用Python3.6面向对象编程语言特性,借助其高效、简洁、灵活等特点,结合Python3.6提供的Padas、matplotlib等模块提供的强大功能,编程实现对判定系数的计算,调用库函数对多元线性回归模型进行训练、评分、预测,得到了较为理想的预测结果,该预测结果在指导投资人在蛋糕房选址上提供了重要的参考价值。结果进一步表明,利用Python 3.6的高效性和强大的扩展性,使得其在多元线性回归模型及数据挖掘领域的其他模型使用中均有极大应用潜力。By establishing multiple linear regression analysis model, using the method of data analysis in the theory of data mining to extract the characteristics of the cake shop month turnover factors, determine the distance and the station nearest store area as characteristic factor, which month turnover to make predictions on the cake.Using Python3.6 object-oriented programming lan-guage features, with the aid of its characteristics such as high efficiency, simple, flexible, combining Python3.6 Padas, matplotlib module provides powerful functions, such as programming to determine the calculation of the coefficient, call library functions for training, score, multiple linear regression model, the ideal prediction results, the predicted results in guiding the investors in the cake room provides an important reference value on the site.The results show that the high efficiency and strong expansibility of Py-thon 3.6 have great potential in the use of multiple linear regression models and other models in data mining.

关 键 词：教学实验 多元线性回归 数据挖掘 数据分析 预测 

分 类 号：G424[文化科学—课程与教学论]