1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135
|
# ggplot backend for the xgboost plotting facilities
#' @rdname xgb.plot.importance
#' @export
xgb.ggplot.importance <- function(importance_matrix = NULL, top_n = NULL, measure = NULL,
rel_to_first = FALSE, n_clusters = c(1:10), ...) {
importance_matrix <- xgb.plot.importance(importance_matrix, top_n = top_n, measure = measure,
rel_to_first = rel_to_first, plot = FALSE, ...)
if (!requireNamespace("ggplot2", quietly = TRUE)) {
stop("ggplot2 package is required", call. = FALSE)
}
if (!requireNamespace("Ckmeans.1d.dp", quietly = TRUE)) {
stop("Ckmeans.1d.dp package is required", call. = FALSE)
}
clusters <- suppressWarnings(
Ckmeans.1d.dp::Ckmeans.1d.dp(importance_matrix$Importance, n_clusters)
)
importance_matrix[, Cluster := as.character(clusters$cluster)]
plot <-
ggplot2::ggplot(importance_matrix,
ggplot2::aes(x = factor(Feature, levels = rev(Feature)), y = Importance, width = 0.5),
environment = environment()) +
ggplot2::geom_bar(ggplot2::aes(fill = Cluster), stat = "identity", position = "identity") +
ggplot2::coord_flip() +
ggplot2::xlab("Features") +
ggplot2::ggtitle("Feature importance") +
ggplot2::theme(plot.title = ggplot2::element_text(lineheight = .9, face = "bold"),
panel.grid.major.y = ggplot2::element_blank())
return(plot)
}
#' @rdname xgb.plot.deepness
#' @export
xgb.ggplot.deepness <- function(model = NULL, which = c("2x1", "max.depth", "med.depth", "med.weight")) {
if (!requireNamespace("ggplot2", quietly = TRUE))
stop("ggplot2 package is required for plotting the graph deepness.", call. = FALSE)
which <- match.arg(which)
dt_depths <- xgb.plot.deepness(model = model, plot = FALSE)
dt_summaries <- dt_depths[, .(.N, Cover = mean(Cover)), Depth]
setkey(dt_summaries, 'Depth')
if (which == "2x1") {
p1 <-
ggplot2::ggplot(dt_summaries) +
ggplot2::geom_bar(ggplot2::aes(x = Depth, y = N), stat = "Identity") +
ggplot2::xlab("") +
ggplot2::ylab("Number of leafs") +
ggplot2::ggtitle("Model complexity") +
ggplot2::theme(
plot.title = ggplot2::element_text(lineheight = 0.9, face = "bold"),
panel.grid.major.y = ggplot2::element_blank(),
axis.ticks = ggplot2::element_blank(),
axis.text.x = ggplot2::element_blank()
)
p2 <-
ggplot2::ggplot(dt_summaries) +
ggplot2::geom_bar(ggplot2::aes(x = Depth, y = Cover), stat = "Identity") +
ggplot2::xlab("Leaf depth") +
ggplot2::ylab("Weighted cover")
multiplot(p1, p2, cols = 1)
return(invisible(list(p1, p2)))
} else if (which == "max.depth") {
p <-
ggplot2::ggplot(dt_depths[, max(Depth), Tree]) +
ggplot2::geom_jitter(ggplot2::aes(x = Tree, y = V1),
height = 0.15, alpha = 0.4, size = 3, stroke = 0) +
ggplot2::xlab("tree #") +
ggplot2::ylab("Max tree leaf depth")
return(p)
} else if (which == "med.depth") {
p <-
ggplot2::ggplot(dt_depths[, median(as.numeric(Depth)), Tree]) +
ggplot2::geom_jitter(ggplot2::aes(x = Tree, y = V1),
height = 0.15, alpha = 0.4, size = 3, stroke = 0) +
ggplot2::xlab("tree #") +
ggplot2::ylab("Median tree leaf depth")
return(p)
} else if (which == "med.weight") {
p <-
ggplot2::ggplot(dt_depths[, median(abs(Weight)), Tree]) +
ggplot2::geom_point(ggplot2::aes(x = Tree, y = V1),
alpha = 0.4, size = 3, stroke = 0) +
ggplot2::xlab("tree #") +
ggplot2::ylab("Median absolute leaf weight")
return(p)
}
}
# Plot multiple ggplot graph aligned by rows and columns.
# ... the plots
# cols number of columns
# internal utility function
multiplot <- function(..., cols = 1) {
plots <- list(...)
num_plots <- length(plots)
layout <- matrix(seq(1, cols * ceiling(num_plots / cols)),
ncol = cols, nrow = ceiling(num_plots / cols))
if (num_plots == 1) {
print(plots[[1]])
} else {
grid::grid.newpage()
grid::pushViewport(grid::viewport(layout = grid::grid.layout(nrow(layout), ncol(layout))))
for (i in 1:num_plots) {
# Get the i,j matrix positions of the regions that contain this subplot
matchidx <- as.data.table(which(layout == i, arr.ind = TRUE))
print(
plots[[i]], vp = grid::viewport(
layout.pos.row = matchidx$row,
layout.pos.col = matchidx$col
)
)
}
}
}
globalVariables(c(
"Cluster", "ggplot", "aes", "geom_bar", "coord_flip", "xlab", "ylab", "ggtitle", "theme",
"element_blank", "element_text", "V1", "Weight"
))
|