Difference between revisions of "Feed Forward Neural Networks"
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**Regularization - Check this box to enable "regularization." This reformulates the performance function as P = g*mse + (1-g)*msw where mse is the mean sum of squares of network errors, msw is the mean sum of squares of network weights and biases, and g is the performance ratio. You can specify the value of g using the edit box to the right of the word "Regularization". This value must be between 0 and 1. A value of 1 is equivalent to unchecking the regularization box. | **Regularization - Check this box to enable "regularization." This reformulates the performance function as P = g*mse + (1-g)*msw where mse is the mean sum of squares of network errors, msw is the mean sum of squares of network weights and biases, and g is the performance ratio. You can specify the value of g using the edit box to the right of the word "Regularization". This value must be between 0 and 1. A value of 1 is equivalent to unchecking the regularization box. | ||
| + | ***Note: If you are using the Bayesian Regularization training algorithm, it will automatically control the regularization and the value you enter in this box doesn't matter (it also doesn't matter whether you check the Regularization box or not). | ||
Revision as of 11:52, 9 June 2012
Introduction
Model Settings
- Improved Generalization
- Regularization - Check this box to enable "regularization." This reformulates the performance function as P = g*mse + (1-g)*msw where mse is the mean sum of squares of network errors, msw is the mean sum of squares of network weights and biases, and g is the performance ratio. You can specify the value of g using the edit box to the right of the word "Regularization". This value must be between 0 and 1. A value of 1 is equivalent to unchecking the regularization box.
- Note: If you are using the Bayesian Regularization training algorithm, it will automatically control the regularization and the value you enter in this box doesn't matter (it also doesn't matter whether you check the Regularization box or not).
- Regularization - Check this box to enable "regularization." This reformulates the performance function as P = g*mse + (1-g)*msw where mse is the mean sum of squares of network errors, msw is the mean sum of squares of network weights and biases, and g is the performance ratio. You can specify the value of g using the edit box to the right of the word "Regularization". This value must be between 0 and 1. A value of 1 is equivalent to unchecking the regularization box.
