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Portable Network Graphic  |  1994-04-29  |  94KB  |  816x1056  |  8-bit (256 colors)
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OCR: Nonlinear Fitting: Solution TAble SSE shows the residual sum Q squares error SSE is the objective that is to be minimi ized. custom loss function is specified, this IS the loss. DFE IS the degrees of freedom for error which is the num iber of observations used minus the number parameters fitted. MSE shows the mean squared error lf the estimate of the variance of the residual error which C the SSE divided by the DFE RMSE estimates of the standard deviation of the residual error, which is square root of the MSE described above Parameter lists the names you gave the parameters in the fitting formula Estimate lists the estimate produced, the process converged ApproxStdErr lists the approximate standard error, which computed analoaouslv to linear regression. It formed by the product of the RMSE ...