Jane Shevtsov wrote:
I am trying to use the plotmo package to generate a partial dependence
plot
for a CART model created with rpart. When running plotmo, I get "Error:
get.plotmo.y returned the wrong length (got 204938 expected 205000)". The
rpart predict function does indeed return 204938 res
Paul Johnson wrote:
m1 <- lm(log(y) ~ log(x), data = dat)
termplot shows log(y) on the vertical. What if I want y on the vertical?
plotmo in the plotmo package has an inverse.func argument,
so something like the following might work for you?
library(MASS)
library(plotmo)
log.brain <- log(An
Johann Hibschman wrote:
I'm having trouble calling randomForest::partialPlot programmatically.
It tries to use name of the (R) variable as the data column name.
You may want to consider looking at plotmo (in the plotmo package) which
doesn't have the above issue.
library(randomForest)
library
"Brian Jensvold" het geskryf
I am trying to create a classification tree using either tree or rpart
but when it comes to plotting the results the formatting I get is
different than what I see in all the tutorials. What I would like to
see is the XX/XX format but all I get is a weird decimal val
Jay het geskryf
When I have made a decision tree with rpart, is it possible to "apply"
this tree to a new set of data in order to find out the distribution
of observations? Ideally I would like to plot my original tree, with
the counts (at each node) of the new data.
Sadly, neither plot.rpart
Jay wrote:
While I'm very pleased with the results I get with rpart and
rpart.plot, I would like to change the scientific notation of the
dependent variable in the plots into integers. Right now all my 5 or
more digit numbers are displayed using scientific notation.
One way of getting rpart.pl
On 2011-07-28 12:14:32, Cleber N.Borges wrote:
I am tring make a simple surface plot ( 2 by 2 terms of a MARS model
(with earth package) but I get the follow error message:
> library( earth )
> data( gasoline, package='pls' )
> nir <- gasoline$NIR
> class( nir )
[1] "AsIs"
> oct <- gasol
On 2011-01-27 14:22, Rasti Matus wrote:
I have a few questions regarding machine learning packages in R,
e.g. earth package ...
1) How could I force the algorithm to generate knots only with
values < 90 for variable doy?
Not possible in the current implementation. In principle it
would be po
| I'm trying to use mars function in R to interpolate nonlinear
| multivariate functions.
| However, it seems that mars gives me a fit which uses only very few
| basis function and it underfits very badly.
Try the "earth" package which extends the mars function in the mda package.
Your example be
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