+ geom_ribbon(stat = "smooth",
se = TRUE,
alpha = 0, # or, use fill = NA
colour = "black",
linetype = "dotted")
Does that work?
On Sat, 12 Aug 2023, 06:12 Rui Barradas, wrote:
> Às 05:17 de 12/08/2023, Thomas Subia via R-help escreveu:
>
G'day Thomas,
On Sat, 12 Aug 2023 04:17:42 + (UTC)
Thomas Subia via R-help wrote:
> Here is my reproducible code for a graph using geom_smooth
The call "library(tidyverse)" was missing. :)
> I'd like to add a black boundary around the shaded area. I suspect
> this can be done with geom_rib
Às 05:17 de 12/08/2023, Thomas Subia via R-help escreveu:
Colleagues,
Here is my reproducible code for a graph using geom_smooth
set.seed(55)
scatter_data <- tibble(x_var = runif(100, min = 0, max = 25)
,y_var = log2(x_var) + rnorm(100))
library(ggplot2)
library(cowplot)
Colleagues,
Here is my reproducible code for a graph using geom_smooth
set.seed(55)
scatter_data <- tibble(x_var = runif(100, min = 0, max = 25)
,y_var = log2(x_var) + rnorm(100))
library(ggplot2)
library(cowplot)
ggplot(scatter_data,aes(x=x_var,y=y_var))+
geom_point()+
Thank you Bert and Ivan,
I was building the SVM model in hopes of applying it to future cases and hoped
that the model would be able to deal with new words it hadn't encountered
during training. But I tried Bert's suggestion by converting all of the data
to tokens, creating a DTM, transformin
В Fri, 11 Aug 2023 10:20:27 +
James C Schopf пишет:
> > train_text_dtm <-
> > DocumentTermMatrix(Corpus(VectorSource(all_train_tokens)))
> > test_text_dtm <-
> > DocumentTermMatrix(Corpus(VectorSource(all_test_tokens)))
I understand the need to prepare the test dataset separately
(e.g. in
I know nothing about tf, etc., but can you not simply read in the whole
file into R and then randomly split using R? The training and test sets
would simply be defined by a single random sample of subscripts which is
either chosen or not.
e.g. (simplified example -- you would be subsetting the row
Hello, I'd be very grateful for your help.
I randomly separated a .csv file with 1287 documents 75%/25% into 2 csv files,
one for training an algorithm and the other for testing the algorithm. I
applied similar preprocessing, including TFIDF transformation, to both sets,
but R won't let me mak
Thank you for your hints.
All of them have been useful, and you solved my problem.
I understood the role of rle, but I think that for my task its use is not
fundamental.
I will put more attention on looking for the existing documentation.
Thank you again
Stefano
(oo)
--oOO--( )--O
I have entered values into Excel, and sorted them. I am assuming you are asking
why the value 3 in x2 is ranked 4.5 versus in x5 it has a rank of 5.
X2 looks like this
Value RankOrder
1 1.5 1
1 1.5 2
2 3 3
3 4.5 4
3 4.5 5
4 6 6
Dear Chris,
the members of the triplet would be ranked 4, 5 and 6 (in your example),
so the *mean of their ranks* is correctly 5.
For any set of k tied values the ranks of its elements are averaged (and
assigned to each of its k members).
Hth -- Gerrit
--
Às 08:20 de 11/08/2023, Sigbert Klinke escreveu:
Hello,
I have defined a function 'equations(...)' which returns an object with
class 'equations'. I also defined a function 'print.equations' which
prints the object. But I did not use 'equations <- function(x, ...)
UseMethod("equations"). Two
I understand that the default ties.method is "average". Here is what I
get, expanding a bit on the help page example. Running R 4.3.1 on Ubuntu
22.04.2.
> x2 <- c(3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5)
> rank(x2)
[1] 4.5 1.5 6.0 1.5 8.0 11.0 3.0 10.0 8.0 4.5 8.0
OK so the ties, each of wi
On Fri, 11 Aug 2023 09:20:03 +0200
Sigbert Klinke wrote:
> I have defined a function 'equations(...)' which returns an object
> with class 'equations'.
> But I did not use 'equations <- function(x, ...)
> UseMethod("equations"). Two questions:
>
> 1.) Is this a sensible approach?
Quite. If the
Hello,
I have defined a function 'equations(...)' which returns an object with
class 'equations'. I also defined a function 'print.equations' which
prints the object. But I did not use 'equations <- function(x, ...)
UseMethod("equations"). Two questions:
1.) Is this a sensible approach?
2.)
15 matches
Mail list logo
