Data structure with the projected and boundary by node and class.

Usage

ternary_str(ppf, id, sp, dx, dy)

Arguments

ppf: is a PPforest object
id: is a vector with the selected projection directions
sp: is the simplex dimensions, if k is the number of classes sp = k - 1
dx: first direction included in id
dy: second direction included in id

Value

Data frame needed to visualize a ternary plot

References

da da Silva, N., Cook, D. & Lee, EK. Interactive graphics for visually diagnosing forest classifiers in R. Comput Stat 40, 3105–3125 (2025). https://doi.org/10.1007/s00180-023-01323-x

Examples

#crab data set with all the observations used as training
pprf.crab <- PPforest(data = crab, std ='min-max', y = "Type",
 size.tr = 1, m = 100, size.p = .5, PPmethod = 'LDA')
 require(dplyr)
#> Loading required package: dplyr
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
pl_ter <- function(dat, dx, dy ){
  p1  <- dat[[1]] %>% dplyr::filter(pair %in% paste(dx, dy, sep = "-") ) %>%
    dplyr::select(Class, x, y) %>%
    ggplot2::ggplot(ggplot2::aes(x, y, color = Class)) +
    ggplot2::geom_segment(data = dat[[2]], ggplot2::aes(x = x1, xend = x2,
                                               y = y1, yend = y2), color = "black" ) +
    ggplot2::geom_point(size = I(3), alpha = .5) +
    ggplot2::labs(y = " ",  x = " ") +
    ggplot2::theme(legend.position = "none", aspect.ratio = 1) +
    ggplot2::scale_colour_brewer(type = "qual", palette = "Dark2") +
    ggplot2::labs(x = paste0("T", dx, " "), y = paste0("T", dy, " ")) +
    ggplot2::theme(aspect.ratio = 1)
  p1
}
#ternary plot in tree different selected dierections
 pl_ter(ternary_str(pprf.crab, id = c(1, 2, 3), sp = 3, dx = 1, dy = 2), 1, 2 )