什么是多项式回归模型？

Multi-variate polynomials are curves which can be used to represent non-linear relationship between a dependent variable and multiple independent variables. A polynomial regression or curve-fitting technique is used to generate a set of equations that represent the non-linear relationship between these variables. The multi-variate nature of the polynomial regression model makes it a powerful tool for a wide range of applications, from financial modelling to image processing. The model is typically fit using least squares regression or other optimization techniques. Although sometimes complex to compute, polynomial regression can provide greater accuracy than simpler linear regression models for predicting outcomes.

提问时间：2023-06-13 19:00:02 编辑时间：2023-06-13 19:00:04 提问者： Ghost_Rider
  • Moonlit_Mask
    1

    简单地说，多项式回归模型是一种曲线拟合方法，可以用于表示依赖变量和多个独立变量之间的非线性关系。该模型通常使用最小二乘回归或其他优化技术进行拟合。尽管计算有时比较复杂，但多项式回归模型可以比简单线性回归模型更精确地预测结果。这种模型在金融建模和图像处理等各种应用中都可以发挥强大的作用。

    回答时间：2023-06-13 19:00:07
相关标签

多项式回归 机器学习 数据建模 非线性回归