Optimal number for speculative rounds in forward selection
Newbie
Hi,
I am applying forward selection in developing SVM model. In the forward selection sub-process, I am applying 5 folds cross-validation. My questions are:
1. May I know what is thebest / optimal number of speculative roundsin forward selection? Any articles that I can refer to as a guide?
It looks like the process non-stop when I use the default parameter, which the speculative round is set to 0, max no of attributes = 10, stopping behavior = without increase.
2. Based on the guide, if the speculative rounds is set to a value higher than 1, it will avoid getting stuck in the local optima. What does that means?
希望Rapidminer专家可以帮助我on this matter. Many thanks in advance.
I am applying forward selection in developing SVM model. In the forward selection sub-process, I am applying 5 folds cross-validation. My questions are:
1. May I know what is thebest / optimal number of speculative roundsin forward selection? Any articles that I can refer to as a guide?
It looks like the process non-stop when I use the default parameter, which the speculative round is set to 0, max no of attributes = 10, stopping behavior = without increase.
2. Based on the guide, if the speculative rounds is set to a value higher than 1, it will avoid getting stuck in the local optima. What does that means?
希望Rapidminer专家可以帮助我on this matter. Many thanks in advance.
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