matlab2012 toolbox 曲线拟合
2016-01-06 20:51
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操作步骤:
如下图
matlab->start->Curve Fitting ->Curve Fitting Tool(cftool)打开曲线拟合的界面,如下图
选择X、Y、Z轴的数据,此处不在赘述。
Custom Equation:自定义公式
Interpolant:插值函数
Nearest neighbor:最近邻居;
Linear:线性;
Cubic:立方体;
Lowess(这个不太清楚);
Polynomial:多项式;
SSE (趋向0最好)– The sum of squares due to error. This statistic measures the deviation of the responses from the fitted values of the responses. A value closer to 0 indicates a better fit.
R-square(趋向1最好) – The coefficient of multiple determination. This statistic measures how successful the fit is in explaining the variation of the data. A value closer to 1 indicates a better fit.
Adjusted R-square(趋向1最好) – The degree of freedom adjusted R-square. A value closer to 1 indicates a better fit. It is generally the best indicator of the fit quality when you add additional coefficients to your model.
RMSE(趋向0最好) – The root mean squared error. A value closer to 0 indicates a better fit.
如下图
matlab->start->Curve Fitting ->Curve Fitting Tool(cftool)打开曲线拟合的界面,如下图
选择X、Y、Z轴的数据,此处不在赘述。
Custom Equation:自定义公式
Interpolant:插值函数
Nearest neighbor:最近邻居;
Linear:线性;
Cubic:立方体;
Lowess(这个不太清楚);
Polynomial:多项式;
SSE (趋向0最好)– The sum of squares due to error. This statistic measures the deviation of the responses from the fitted values of the responses. A value closer to 0 indicates a better fit.
R-square(趋向1最好) – The coefficient of multiple determination. This statistic measures how successful the fit is in explaining the variation of the data. A value closer to 1 indicates a better fit.
Adjusted R-square(趋向1最好) – The degree of freedom adjusted R-square. A value closer to 1 indicates a better fit. It is generally the best indicator of the fit quality when you add additional coefficients to your model.
RMSE(趋向0最好) – The root mean squared error. A value closer to 0 indicates a better fit.
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