基于Python的线性回归性能分析

Performance Analysis of Linear Regression Based on Python

Python语言因为简洁、易读以及扩展性强的特点,成为当下最流行的机器学习语言,通过扩展库NumPy,可以实现快速数组处理功能。同时,Python通过扩展TensorFlow框架,可以直接实现TensorFlow框架的机器学习,但是存在缺少定量分析的问题。文章通过模拟不同数量的数据,分别用NumPy库和TensorFlow框架来实现线性回归,通过比较相同的迭代次数的计算时间,相同的迭代精度的迭代次数的分析,给出了定量数据分析,为NumPy库和TensorFlow框架实践应用提供一定的参考依据。

Python language is the most popular machine learning language because of its simplicity,reading easily and strong extensibility.By expanding library NumPy,we can realize fast array processing.At the same time,Python can directly implement machine learning of the TensorFlow framework by extending the TensorFlow framework,but there is a lack of quantitative analysis.By simulating different amounts of data,this paper respectively use NumPy library and TensorFlow Frameworks to realize linear regression.By comparing the calculation time of the same number of iterations and the analysis of the same number of iterations with the same iteration precision,,quantitative data analysis is given,which provides certain reference for the practical application of NumPy library and TensorFlow framework.