The error function is the sum of squared errors
between the network outputs and the target values, computed as in Equation (5).
0's) and then using Solver to achieve a minimum value of the sum of squared error
term (SSE; cell E2; highlighted in red).
In these months, a big part of the total sum of squared errors
occurs in the first four months of recessions.
The sum of squared errors
is minimized by equating the derivative of the squared errors to zero.
4) Convergence is monitored by observing sum of squared errors
of the observed values and corresponding predicted values from step (2).
M taken in the same [DELTA]t interval-minimizing the sum of squared errors
[between observed ([E.
MARS would take money growth, output growth, and the rate of currency depreciation as predictors and attempt to fit the best model for the inflation rate by placing knots and choosing additive and interactive effects to minimize the sum of squared errors
Learning is complete when no further reduction in the sum of squared errors
xB[left arrow]C * X to create the B-coefficients, the predicted C values, CH, the errors, E, and the sum of squared errors
, SSE, in one step.