R help - Jul 2008 - predict rpart: new data has new level

Hi.  I uses rpart to build a regression tree.  Y is continuous. Now, I try
   to predict on a new set of data.  In the new set of data, one of my x (call
   Incoterm, a factor) has a new level.
   I  wonder  why the  error  below appears as the guide says "For factor
   predictors, if an observation contains a level not used to grow the tree, it
   is left at the deepest possible node and frame$yval at the node is the
   prediction. "
   Many thanks.
   > mod <- rpart(y~., data=data.frame(y=y,x=x), method="anova",
   +                       cp=0.05, minsplit=100, minbucket=50, maxdepth=5)
   > predictLost  <-  predict(mod,  newdata=data.frame(y=yLost, x=xLost),
   type="vector")
   Error  in  model.frame.default(Terms, newdata, na.action = act, xlev   
attr(object,  :
     factor 'x.Incoterm' has new level(s) MTD
   ----
   Chua Siang Li
   Consultant - Operations Research
   Acceval Pte Ltd
   Tel: 6297 8740
   Email: siang.li.chua at acceval-intl.com
   Website: www.acceval-intl.com
   This message and any attachments (the "message"...{{dropped:13}}

On Thu, 31 Jul 2008, Chua Siang Li wrote:
>
>   Hi.  I uses rpart to build a regression tree.  Y is continuous. Now, I
try
>   to predict on a new set of data.  In the new set of data, one of my x
(call
>   Incoterm, a factor) has a new level.
>   I  wonder  why the  error  below appears as the guide says "For
factor
>   predictors, if an observation contains a level not used to grow the tree,
it
>   is left at the deepest possible node and frame$yval at the node is the
>   prediction. "
That's about a level defined in the factor passed to rpart but not present 
in the data, not a level not present in the factor in the original data. 
E.g. if 'fruit' has levels apple, orange, lemon and there were no
oranges
in the training set.  Your situation is that you asked for predictions on 
pears.
>   Many thanks.
>   > mod <- rpart(y~., data=data.frame(y=y,x=x),
method="anova",
>   +                       cp=0.05, minsplit=100, minbucket=50, maxdepth=5)
>   > predictLost  <-  predict(mod,  newdata=data.frame(y=yLost,
x=xLost),
>   type="vector")
>   Error  in  model.frame.default(Terms, newdata, na.action = act, xlev >
attr(object,  :
>     factor 'x.Incoterm' has new level(s) MTD
>   ----
>   Chua Siang Li
>   Consultant - Operations Research
>   Acceval Pte Ltd
>   Tel: 6297 8740
>   Email: siang.li.chua at acceval-intl.com
>   Website: www.acceval-intl.com
>   This message and any attachments (the
"message"...{{dropped:13}}
> ______________________________________________
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>
-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595