new function cv.importance + documentation

R-package/R/xgb.importance.R

@@ -0,0 +1,54 @@
+#' Show importance of features in a model
+#' 
+#' Read a xgboost model in text file format. Return a data.table of the features with their weight.
+#' 
+#' @importFrom data.table data.table
+#' @importFrom magrittr %>%
+#' @importFrom data.table :=
+#' @param feature_names names of each feature as a character vector. Can be extracted from a sparse matrix.
+#' @param filename_dump the name of the text file.
+#'
+#' @examples
+#' data(agaricus.train, package='xgboost')
+#' data(agaricus.test, package='xgboost')
+#' 
+#' #Both dataset are list with two items, a sparse matrix and labels (outcome column which will be learned). 
+#' #Each column of the sparse Matrix is a feature in one hot encoding format.
+#' train <- agaricus.train
+#' test <- agaricus.test
+#' 
+#' bst <- xgboost(data = train$data, label = train$label, max.depth = 2, 
+#'                eta = 1, nround = 2,objective = "binary:logistic")
+#' xgb.dump(bst, 'xgb.model.dump')
+#' 
+#' #agaricus.test$data@@Dimnames[[2]] represents the column name of the sparse matrix.
+#' xgb.importance(agaricus.test$data@@Dimnames[[2]], 'xgb.model.dump')
+#' 
+#' @export
+xgb.importance <- function(feature_names, filename_dump){  
+  text <- readLines(filename_dump)  
+  if(text[2] == "bias:"){
+    result <- linearDump(feature_names, text)
+  }  else {
+    result <- treeDump(feature_names, text)
+  }
+  result
+}
+
+treeDump <- function(feature_names, text){  
+  result <- c()
+  for(line in text){
+    m <- regexec("\\[f.*\\]", line)
+    p <- regmatches(line, m)
+    if (length(p[[1]]) > 0) {      
+      splits <- as.numeric(strsplit(sub("\\]", "", sub("\\[f", "", p[[1]])), "<")[[1]])
+      result <- c(result, feature_names[splits[1]+ 1])
+    }
+  }
+  #1. Reduce, 2. %, 3. remove temp col, 4. reorder - bigger top
+  data.table(Feature = result)[,.N, by = Feature][, Weight:= N /sum(N)][order(-rank(Weight))][,-2,with=F]
+}
+
+linearDump <- function(feature_names, text){
+  which(text == "weight:") %>% {a=.+1;text[a:length(text)]} %>% as.numeric %>% data.table(Feature = feature_names, Weight = .)
+}