visTree {visNetwork} | R Documentation |
Visualize Recursive Partitioning and Regression Trees (rpart object)
Description
Visualize Recursive Partitioning and Regression Trees rpart
. Have a look to visTreeEditor to edity and get back network, or to visTreeModuleServer to use custom tree module in R
Usage
visTree(
object,
data = NULL,
tooltipColumns = if (!is.null(data)) { 1:ncol(data) } else { NULL },
main = "",
submain = "",
footer = "",
direction = "UD",
fallenLeaves = FALSE,
rules = TRUE,
simplifyRules = TRUE,
shapeVar = "dot",
shapeY = "square",
colorVar = NULL,
colorY = NULL,
colorEdges = "#8181F7",
nodesFontSize = 16,
edgesFontSize = 14,
edgesFontAlign = "horizontal",
legend = TRUE,
legendNodesSize = 22,
legendFontSize = 16,
legendWidth = 0.1,
legendNcol = 1,
legendPosition = "left",
nodesPopSize = FALSE,
minNodeSize = 15,
maxNodeSize = 30,
highlightNearest = list(enabled = TRUE, degree = list(from = 50000, to = 0), hover =
FALSE, algorithm = "hierarchical"),
collapse = list(enabled = TRUE, fit = TRUE, resetHighlight = TRUE, clusterOptions =
list(fixed = TRUE, physics = FALSE)),
updateShape = TRUE,
tooltipDelay = 500,
digits = 3,
height = "600px",
width = "100%",
export = TRUE
)
Arguments
object |
|
data |
|
tooltipColumns |
|
main |
Title. See visNetwork |
submain |
Subtitle. See visNetwork |
footer |
Footer. See visNetwork |
direction |
|
fallenLeaves |
|
rules |
|
simplifyRules |
|
shapeVar |
|
shapeY |
|
colorVar |
|
colorY |
if classification tree :
if regression tree : |
colorEdges |
|
nodesFontSize |
|
edgesFontSize |
|
edgesFontAlign |
|
legend |
|
legendNodesSize |
|
legendFontSize |
|
legendWidth |
|
legendNcol |
|
legendPosition |
|
nodesPopSize |
|
minNodeSize |
|
maxNodeSize |
|
highlightNearest |
|
collapse |
|
updateShape |
|
tooltipDelay |
|
digits |
|
height |
|
width |
|
export |
|
Value
a visNetwork object
References
See online documentation https://datastorm-open.github.io/visNetwork/
See Also
visTreeEditor, visTreeModuleServer, visNetworkEditor
Examples
## Not run:
library(rpart)
# Basic classification tree
res <- rpart(Species~., data=iris)
visTree(res, data = iris, main = "Iris classification Tree")
# Basic regression tree
res <- rpart(Petal.Length~., data=iris)
visTree(res, edgesFontSize = 14, nodesFontSize = 16)
# Complex tree
data("solder")
res <- rpart(Opening~., data = solder, control = rpart.control(cp = 0.00005))
visTree(res, data = solder, nodesPopSize = TRUE, minNodeSize = 10,
maxNodeSize = 30, height = "800px")
# ----- Options
res <- rpart(Opening~., data = solder, control = rpart.control(cp = 0.005))
# fallen leaves + align edges label & size
visTree(res, fallenLeaves = TRUE, height = "500px",
edgesFontAlign = "middle", edgesFontSize = 20)
# disable rules in tooltip, and render tooltip faster
# enable hover highlight
visTree(res, rules = FALSE, tooltipDelay = 0,
highlightNearest = list(enabled = TRUE, degree = list(from = 50000, to = 0),
hover = TRUE, algorithm = "hierarchical"))
# Change color with data.frame
colorVar <- data.frame(variable = names(solder),
color = c("#339933", "#b30000","#4747d1","#88cc00", "#9900ff","#247856"))
colorY <- data.frame(modality = unique(solder$Opening),
color = c("#AA00AA", "#CDAD15", "#213478"))
visTree(res, colorEdges = "#000099", colorVar = colorVar, colorY = colorY)
# Change color with vector
visTree(res, colorEdges = "#000099",
colorVar = substring(rainbow(6), 1, 7),
colorY = c("blue", "green", "orange"))
# Use visNetwork functions to add more options
visTree(res) %>%
visOptions(highlightNearest = TRUE)
## End(Not run)