Hi All,
I have just started my advanced statistics study. And here is one thing I have not been able to understand for long time -- how can we pre-determine the range of testing tuning parameters in cross validation if we do not want R automatically select them? I saw some paper says using a log scale. I am not so clear about that. In that case, how to ensure the precision of the best one since our test is done at a very sparse scale.
Can someone tell about this? If the strategy is not universal, you can take ridge or lasso for examples. And would be better to have some links to literature.
many thanks
I have just started my advanced statistics study. And here is one thing I have not been able to understand for long time -- how can we pre-determine the range of testing tuning parameters in cross validation if we do not want R automatically select them? I saw some paper says using a log scale. I am not so clear about that. In that case, how to ensure the precision of the best one since our test is done at a very sparse scale.
Can someone tell about this? If the strategy is not universal, you can take ridge or lasso for examples. And would be better to have some links to literature.
many thanks