Just re-read your question and realized I misread the error message.
The argument is of zero length.
But the conclusion is the same, either a bug in the package, or a
problem with your input.
On Fri, Aug 21, 2020 at 4:16 PM Abby Spurdle wrote:
>
> Note that I'm not familiar with this package
Note that I'm not familiar with this package or the method.
Also note that you haven't told anyone what function you're using, or
what your call was.
I'm assuming that you're using the rotationForest() function.
According to its help page, the default is:
K = round(ncol(x)/3, 0)
There's no
Hi R Helpers,
I wanted to try the rotationForest package.
I pointed it at my data set and got the error message "Error in if (K >=
ncol(x)) stop("K should not be greater than or equal to the number of columns
in x") :
argument is of length zero'.
My dataset has 3688 obs. of 111 variables.
The single grep regex solutions offered to Ivan's problem were fine, but do
not readily generalize to the conjunction of multiple (>2, say) regex
patterns that can appear anywhere in a string and in any order. However,
note that this can easily be done using the Perl zero width lookahead
On Wed, Aug 19, 2020 at 10:03 AM Ivan Calandra wrote:
>
> Dear useRs,
>
> I'm new to the tidyverse world and I need some help on basic things.
>
> I have the following tibble:
> mytbl <- structure(list(files = c("a", "b", "c", "d", "e", "f"), prop =
> 1:6), row.names = c(NA, -6L), class =
Buenas tardes, tengo una variable bimodal (*var)*, de presencias y
ausencias (1s y 0s) y otra variable, *prob*, con las probabilidades (entre
0 y 1) que le asigna un modelo.
Con: *ggplot(Preds, aes(x=prob, fill= var )) + geom_density(alpha=.3)*
obtengo la distribución de las presencias y de las
Dear All,
Allow me to re-introduce the skedastic package (version 1.0.0) which now
implements more than 20 different heteroskedasticity tests for the linear
regression model, as well as a graphical diagnostic tool and some helper
functions with broader applications (e.g., computing probability
Hello,
It is also possible to select by vectors of indices (as opposed to a
vector):
top_n is just to not clutter the display.
library(dplyr)
data(iris)
iris %>% select(1, 3, 4) %>% top_n(5)
iris %>% select(c(1, 3), 4) %>% top_n(5)
Hope this helps,
Rui Barradas
Às 10:05 de 20/08/20,
On 20/08/2020 3:42 a.m., Shaami wrote:
> Hi Dear
>
> I am facing a floating-point problem related to the sum of probabilities.
> It is really difficult to prove that sum of probabilities is 1 because of
> some minor differences. The MWE is as follows.
>
>> p1=0.
>> p2=0.003>
A kind of hybrid answer is to use base::subset(), which supports non-standard
evaluation (it searches for unquoted symbols like 'files' in the code line
below in the object that is its first argument; %>% puts 'mytbl' in that first
position) and row (filter) and column (select) subsets
> mytbl
Hi Dear
I am facing a floating-point problem related to the sum of probabilities.
It is really difficult to prove that sum of probabilities is 1 because of
some minor differences. The MWE is as follows.
> p1=0.
> p2=0.003> p1+p2==1[1] FALSE
The sum of probabilities is
OK, my bad... I'm sure I had tried it and it didn't work, but I guess
the error was somewhere else...
Thank you!
Ivan
--
Dr. Ivan Calandra
TraCEr, laboratory for Traceology and Controlled Experiments
MONREPOS Archaeological Research Centre and
Museum for Human Behavioural Evolution
Schloss
Did you try it?
mydata %>%
select( c( 1, 2, 4 ) )
On August 20, 2020 1:41:13 AM PDT, Ivan Calandra wrote:
>Dear useRs,
>
>I'm still trying to learn tidyverse syntax.
>
>I would like to select() columns based on their positions/indices, but
>I
>cannot find a way to do that (I've seen a lot
Dear useRs,
I'm still trying to learn tidyverse syntax.
I would like to select() columns based on their positions/indices, but I
cannot find a way to do that (I've seen a lot about doing that for rows,
but I could not find anything for columns). I thought it would be
obvious, but I cannot find
Hi Jeff,
The code you show is exactly what I usually do, in base R; but I wanted
to play with tidyverse to learn it (and also understand when it makes
sense and when it doesn't).
And yes, of course, in the example I gave, I end up with a 1-cell
tibble, which could be better extracted as a
Dear Chris,
I didn't think about having the assignment at the end as you showed; it
indeed fits the pipe workflow better.
By "easy", I actually meant shorter. As you said, in base R, I usually
do that in 1 line, so I was hoping to do the same in tidyverse. But I'm
glad to hear that I'm using
Thank you all for all the very helpful answers!
Best,
Ivan
--
Dr. Ivan Calandra
TraCEr, laboratory for Traceology and Controlled Experiments
MONREPOS Archaeological Research Centre and
Museum for Human Behavioural Evolution
Schloss Monrepos
56567 Neuwied, Germany
+49 (0) 2631 9772-243
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