I think the only thing you are doing wrong is not setting the random
seed (set.seed()) so your results are not reproducible. Depending on
the random sample used to select the training and test sets, you get
slightly varying accuracy for both, sometimes one is better and
sometimes the other.
HTH,
Hi ML,
For random forest, I thought that the out-of-bag performance should be
the same (or at least very similar) to the performance calculated on a
separated test set.
But this does not seem to be the case.
In the following code, the accuracy computed on out-of-bag sample is
77.81%, while
Hi Roger,
You could look at the attributes() function in base-R. See:
> ?attributes
>From the help-page:
> ## strip an object's attributes:
> attributes(x) <- NULL
HTH, Bill.
W. Michels, Ph.D.
On Sat, Apr 10, 2021 at 4:20 AM Koenker, Roger W wrote:
>
> Wolfgang,
>
> Thanks, this is
Hello,
The following solution seems to work and is fast, like findInterval is.
It first determines where in df2$start is each value of df1$Time. Then
uses that index to see if those Times are not greater than the
corresponding df$end.
I checked against a small subset of df1 and the results
Wolfgang,
Thanks, this is _extremely_ helpful.
Roger
> On Apr 10, 2021, at 11:59 AM, Viechtbauer, Wolfgang (SP)
> wrote:
>
> Dear Roger,
>
> The problem is this. qss() looks like this:
>
> if (is.matrix(x)) {
> [...]
> }
> if (is.vector(x)) {
> [...]
> }
> qss
>
> Now let's check
Dear all,
I have two data frames (df1 and df2) and for each timepoint in df1 I
want to know: is it whithin any of the timespans in df2? The result
(e.g. "no" or "yes" or 0 and 1) should be shown in a new column of df1
Here is the code to create the two data frames (the size of the two data
Dear Roger,
The problem is this. qss() looks like this:
if (is.matrix(x)) {
[...]
}
if (is.vector(x)) {
[...]
}
qss
Now let's check these if() statements:
is.vector(B$x) # TRUE
is.vector(D$x) # FALSE
is.matrix(B$x) # FALSE
is.matrix(D$x) # FALSE
is.vector(D$x) being FALSE may be
As shown in the reproducible example below, I used the RStudio function haven()
to read a Stata .dta file, and then tried to do some fitting with the resulting
data.frame. This produced an error from my fitting function rqss() in the
package quantreg. After a bit of frustrated cursing, I
Hello,
I believe that the point we are missing is that datatable$column stores
the *names* of the graphs, not the graph objects themselves. So in the
loop the objects must be retrieved with mget() or get().
First create a reproducible example.
library(tidygraph)
my_function <-
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