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Special attention is paid to generalization errors around the optimum.
H. Mhaskar and Poggio, T., "An analysis of training and generalization errors in shallow and deep networks".
The procedure was performed 100 times and the generalization errors were averaged to have an unbiased measure of the performance of the models.
The results of our experiment show that the multiclass SVM-RFE process is not only very useful for identifying critical form features with minimum generalization errors but also can be used to select the smallest feature subset for building a prediction model with a given discrimination capability.
Hence, an accurate generalization error is not critical, while correct relative generalization errors is paramount.
Figure 6 Evolution of training and generalization errors by increasing the number of hidden layers.
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These characteristics enable to approximate complex functions with a generally low generalization error.
average performance is similar to the one from Table 3, which is in line with the general observation that both generalization error and Matthews correlation coefficient can exhibit the same overall predictive power.
Intuitively, a good separation is achieved by the hyperplane that has the largest distance to the nearest training datapoints of any class, since in general the larger the margin the lower the generalization error of the classifier.
We generate a list of candidate parameter values and estimate the expected generalization error resulting from each one; finally, we select the one parameter value that results in the lowest estimated generalization error.
Claude, N. & Bengio, Y. Inference for the generalization error.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com