Hi all -
I am trying to tune an SVM model by optimizing the cross-validation
accuracy. Maximizing this value doesn't necessarily seem to minimize the
number of misclassifications. Can anyone tell me how the
cross-validation accuracy is defined? In the output below, for example,
cross-validation
The 99.7% accuracy you quoted, I take it, is the accuracy on the training
set. If so, that number hardly means anything (other than, perhaps,
self-fulfilling prophecy). Usually what one would want is for the model to
be able to predict data that weren't used to train the model with high
Ton van Daelen wrote:
Hi all -
I am trying to tune an SVM model by optimizing the cross-validation
accuracy. Maximizing this value doesn't necessarily seem to minimize the
number of misclassifications. Can anyone tell me how the
cross-validation accuracy is defined? In the output below, for
