"How can X-Validation use only a training set and give a performance?"
nelsonthekinger
MemberPosts:5
Contributor I
I There I'm a rookie to Rapidminer but there are something that is bugging me.
When we use X-Validation its only required the training set, and in the test side we apply the model and test performance
但如果没有我们如何测试性能any test data?
Does X-Validation train itself with the training set (labeled) and than unlabel the same training set and test its performance?
Thanks a Lot guys
When we use X-Validation its only required the training set, and in the test side we apply the model and test performance
但如果没有我们如何测试性能any test data?
Does X-Validation train itself with the training set (labeled) and than unlabel the same training set and test its performance?
Thanks a Lot guys
Tagged:
0
Answers
Cross validation splits the training data into N partitions and builds a model on N-1 of these to apply to the 1 partition that is left over to create a performance measure. It repeats this N times for the N different individual partitions to obtain N performance measures which it averages. The result is an estimate of how the model would perform on unseen data.
Andrew