[R] "tree": Extracting deviance & Gaussian model of the node?

[Tak Kaneko]

Hi

I'm trying to use the "tree" package in R to predict intonation for a
speech synthesiser and when I feed the feature vector into the tree,
I want to get the predicted value and the deviance associated with that
node.

Q.1
---
I was hoping that the following command will return a tree object of the
predicted values, but I get the following error:

------------------------------------------------------------
> test.tr <- predict.tree(pr,test.data,type="tree")
Error in as.list(X) : Object "response.names" not found

where:
pr = 	A tree was grown using the training data and then pruned back to
	where the deviance was minimised when a separate test data set was
	used. "pr" is this pruned tree.

test.data = test data with the features and response
-------------------------------------------------------------

How would I be able to access the prediction and the deviance? Would this
work if the data was a feature vector with no responses? (as would be the
case when it comes to predicting the real thing).


Q.2
---
Assuming that the distribution of the data at each node is Gaussian, I'd
like to model each node as a gaussian probability density function with a
mean at the predicted value and variance, which is presumably related to
the deviance...

I've found out the definition for the deviance from the S-plus manual but
it's not yet clear to me. So how could I deduce the variance of a value
predicted by "tree"?


Thanks and I'd be grateful if you could also reply to my address above
(tk229 at cam.ac.uk).

Tak Kaneko


--------------------------------------------------------
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Permanent e-mail:	tkaneko at iee.org
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