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Locally weighted polynomial regression LWPR is a popular instance based al gorithm for learning continuous non linear mappings For more than two or three in puts and for more than a few thousand dat apoints the computational expense of pre dic
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强局部加权回归算法由Cleveland[7]提出,主要利用局部观测数据对欲拟合点进行多项式加权拟合,并用最小二乘法进行估计.它综合了传统的局部多项式拟合,局部加权回归以及具有强鲁棒性的拟合过程
-Strong locally weighted regression algorithm by Cleveland [7] proposed, mainly using local observational data points on the polynomial fitting For wei
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多元多项式回归，即一个程序，一个程序，对于给定的数据确定最小误差平方多项式。输出值也可能被转化运用Logit变换，从而使多元logistic回归。如何应用此程序的简要描述，可以发现在C源码包文件中的倒退/ EX / README。-A program for multivariate polynomial regression, i.e., a program that determines a minimum squared error polynomial for given data. T
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线性回归的学习算法。包括数据分析、线性回归、在线梯度下降、多项式回归。压缩包中给出.txt数据文件及说明文档。-Linear regression learning algorithm. Including data analysis, linear regression line gradient descent, polynomial regression. Compressed data given .txt file and documentation.
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这段代码可以实现机器学习中的岭回归。自行添加高斯噪声后对每个数据集的七阶多项式用不同的值λ进行岭回归-Perform ridge regression on each dataset with 7th order polynomial with different value λ.Add Gaussian noise.
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