multi trees

R-package/R/xgb.model.dt.tree.R

@@ -96,13 +96,14 @@ xgb.model.dt.tree <- function(feature_names = NULL, filename_dump = NULL, model
   
   allTrees <- data.table()
  
-  anynumber_regex<-"[-+]?[0-9]*\\.?[0-9]+([eE][-+]?[0-9]+)?" 
+  anynumber_regex <- "[-+]?[0-9]*\\.?[0-9]+([eE][-+]?[0-9]+)?" 
+  
   for(i in 1:n_round){
     
     tree <- text[(position[i]+1):(position[i+1]-1)]
     
     # avoid tree made of a leaf only (no split)
-    if(length(tree) <2) next
+    if(length(tree) < 2) next
     
     treeID <- i-1
     

R-package/R/xgb.plot.multi.tree.R

@@ -0,0 +1,42 @@
+library(stringr)
+library(data.table)
+
+
+
+data(agaricus.train, package='xgboost')
+
+#Both dataset are list with two items, a sparse matrix and labels
+#(labels = outcome column which will be learned).
+#Each column of the sparse Matrix is a feature in one hot encoding format.
+train <- agaricus.train
+
+bst <- xgboost(data = train$data, label = train$label, max.depth = 5,
+               eta = 1, nthread = 2, nround = 2,objective = "binary:logistic")
+
+#agaricus.test$data@Dimnames[[2]] represents the column names of the sparse matrix.
+tree.matrix <- xgb.model.dt.tree(agaricus.train$data@Dimnames[[2]], model = bst)
+
+
+# first number of the path represents the tree, then the following numbers are related to the path to follow
+
+# root init
+root.nodes <- tree.matrix[str_detect(ID, "\\d+-0"), ID]
+tree.matrix[ID == root.nodes, Abs.Position:=root.nodes]
+
+precedent.nodes <- root.nodes
+
+while(tree.matrix[,sum(is.na(Abs.Position))] > 0) {
+  yes.row.nodes <- tree.matrix[Abs.Position %in% precedent.nodes & !is.na(Yes)]
+  no.row.nodes <- tree.matrix[Abs.Position %in% precedent.nodes & !is.na(No)]
+  yes.nodes.abs.pos <- yes.row.nodes[, Abs.Position] %>% paste0("-0")
+  no.nodes.abs.pos <- no.row.nodes[, Abs.Position] %>% paste0("-1")
+  
+  tree.matrix[ID == yes.row.nodes[, Yes], Abs.Position := yes.nodes.abs.pos]
+  tree.matrix[ID == no.row.nodes[, No], Abs.Position := no.nodes.abs.pos]
+  precedent.nodes <- c(yes.nodes.abs.pos, no.nodes.abs.pos)
+}
+
+tree.matrix
+
+
+