I am looking at results of a random forest. In the documentation, it says
the following for categorical variables:
"For categorical predictors, the splitting point is represented by an
integer, whose binary expansion gives the identities of the categories that
goes to left or right. For example, i
On Fri, Aug 14, 2009 at 1:43 PM, Mary Putt wrote:
> I'm not calling it a problem that the answer converges--i.e. that the
> algorithm is stable. but if you look at the example even though I've asked
> for 2000 or 200 tress, ntree=2000 or ntree=200, it still gives me 500 trees
> according to the
On Thu, Aug 13, 2009 at 11:11 PM, Mary Putt wrote:
Hi Mary,
> I would like to use a random Forest model to get an idea about which
> variables from a dataset may have some prognostic significance in a smallish
> study. The default for the number of trees seems to be 500. I tried changing
> the
Hi,
I would like to use a random Forest model to get an idea about which variables
from a dataset may have some prognostic significance in a smallish study. The
default for the number of trees seems to be 500. I tried changing the default
to ntree=2000 or ntree=200 and the results appear ident
Hi,
I am trying to find some information on the strata option in randomForest().
I am hoping to make predictions from some clustered data (many predictors
measured repeatedly on the same subject over time). I would like to apply
random forests or gradient boosting ( gbm() ) to this problem but
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