xgb.plot.tree布局(r)
我正在阅读一个xgb,示例结果中的xgb.plot.tree命令生成如下图片: 然而,当我做同样的事情时,我得到了一张这样的图片,它是两个不同的图形,颜色也不同 这正常吗?这两个图是两棵树吗?我有同样的问题。 根据xgboost github存储库上的一个问题案例,这可能是由于xgboost用于渲染树的图表库发生了更改。 我没有使用diagrammeR命令修改xgb.plot.tree布局(r),r,xgboost,ensemble-learning,R,Xgboost,Ensemble Learning,我正在阅读一个xgb,示例结果中的xgb.plot.tree命令生成如下图片: 然而,当我做同样的事情时,我得到了一张这样的图片,它是两个不同的图形,颜色也不同 这正常吗?这两个图是两棵树吗?我有同样的问题。 根据xgboost github存储库上的一个问题案例,这可能是由于xgboost用于渲染树的图表库发生了更改。 我没有使用diagrammeR命令修改dgr_图形对象,而是选择创建一个新版本的函数xgb.plot.tree,该函数直接定义节点字体的颜色。将参数fontcolor=“
dgr_图形
对象,而是选择创建一个新版本的函数xgb.plot.tree
,该函数直接定义节点字体的颜色。将参数fontcolor=“black”
添加到节点%rev,data=allTrees[,,
功能]]>%rev,fontname=“Helvetica”,fontcolor=“black”)
边%rep(2),所有树[,ID]>%rev),to=匹配(所有树[特征]=
“叶”,c(是,否)],所有树[,ID]>%rev),标签=所有树[特征!=
“叶子”,粘贴(“太棒了!一年后,原来的功能仍然不稳定。”。。
xgb.plot.tree <- function (feature_names = NULL, model = NULL, n_first_tree = NULL,
plot_width = NULL, plot_height = NULL, ...)
{
if (class(model) != "xgb.Booster") {
stop("model: Has to be an object of class xgb.Booster model generaged by the xgb.train function.")
}
if (!requireNamespace("DiagrammeR", quietly = TRUE)) {
stop("DiagrammeR package is required for xgb.plot.tree",
call. = FALSE)
}
allTrees <- xgb.model.dt.tree(feature_names = feature_names,
model = model, n_first_tree = n_first_tree)
allTrees[, `:=`(label, paste0(Feature, "\\nCover: ", Cover,
"\\nGain: ", Quality))]
allTrees[, `:=`(shape, "rectangle")][Feature == "Leaf", `:=`(shape,
"oval")]
allTrees[, `:=`(filledcolor, "Beige")][Feature == "Leaf",
`:=`(filledcolor, "Khaki")]
nodes <- DiagrammeR::create_node_df(n = length(allTrees[,
ID] %>% rev), label = allTrees[, label] %>% rev, style = "filled",
color = "DimGray", fillcolor = allTrees[, filledcolor] %>%
rev, shape = allTrees[, shape] %>% rev, data = allTrees[,
Feature] %>% rev, fontname = "Helvetica", fontcolor="black")
edges <- DiagrammeR::create_edge_df(from = match(allTrees[Feature !=
"Leaf", c(ID)] %>% rep(2), allTrees[, ID] %>% rev), to = match(allTrees[Feature !=
"Leaf", c(Yes, No)], allTrees[, ID] %>% rev), label = allTrees[Feature !=
"Leaf", paste("<", Split)] %>% c(rep("", nrow(allTrees[Feature !=
"Leaf"]))), color = "DimGray", arrowsize = "1.5", arrowhead = "vee",
fontname = "Helvetica", rel = "leading_to")
graph <- DiagrammeR::create_graph(nodes_df = nodes, edges_df = edges)
DiagrammeR::render_graph(graph, width = plot_width, height = plot_height)
}
xgb.plot.tree <- function (feature_names = NULL, model = NULL, n_first_tree = NULL,
plot_width = NULL, plot_height = NULL, ...)
{
if (class(model) != "xgb.Booster") {
stop("model: Has to be an object of class xgb.Booster model generaged by the xgb.train function.")
}
if (!requireNamespace("DiagrammeR", quietly = TRUE)) {
stop("DiagrammeR package is required for xgb.plot.tree",
call. = FALSE)
}
allTrees <- xgb.model.dt.tree(feature_names = feature_names,
model = model, n_first_tree = n_first_tree)
allTrees$Quality <- round(allTrees$Quality, 3)
allTrees$Cover <- round(allTrees$Cover, 3)
allTrees[, `:=`(label, paste0(Feature, "\\nCover: ", Cover,
"\\nGain: ", Quality))]
allTrees[, `:=`(shape, "rectangle")][Feature == "Leaf", `:=`(shape,
"egg")]
allTrees[, `:=`(filledcolor, "Beige")][Feature == "Leaf",
`:=`(filledcolor, "Khaki")]
nodes <- DiagrammeR::create_node_df(n = length(allTrees[,
ID] %>% rev), label = allTrees[, label] %>% rev, style = "filled", width=1.5,
color = "DimGray", fillcolor = allTrees[, filledcolor] %>%
rev, shape = allTrees[, shape] %>% rev, data = allTrees[,
Feature] %>% rev, fontname = "Helvetica", fontcolor="black")
edges <- DiagrammeR::create_edge_df(from = match(allTrees[Feature !=
"Leaf", c(ID)] %>% rep(2), allTrees[, ID] %>% rev), to = match(allTrees[Feature !=
"Leaf", c(Yes, No)], allTrees[, ID] %>% rev), label = allTrees[Feature !=
"Leaf", paste("<", Split)] %>% c(rep("", nrow(allTrees[Feature !=
"Leaf"]))), color = "DimGray", arrowsize = 1, arrowhead = "vee", minlen="5",
fontname = "Helvetica", rel = "leading_to", fontsize="15")
graph <- DiagrammeR::create_graph(nodes_df = nodes, edges_df = edges, attr_theme=NULL)
DiagrammeR::render_graph(graph, width = plot_width, height = plot_height)
return(graph)
}