了解 R 中 xgboost 的 num_classes [英] Understanding num_classes for xgboost in R

问题描述

我在弄清楚如何正确设置 xgboost 的 num_classes 时遇到了很多麻烦.

I'm having a lot of trouble figuring out how to correctly set the num_classes for xgboost.

我有一个使用 Iris 数据的例子

I've got an example using the Iris data

df <- iris

y <- df$Species
num.class = length(levels(y))
levels(y) = 1:num.class
head(y)

df <- df[,1:4]

y <- as.matrix(y)
df <- as.matrix(df)

param <- list("objective" = "multi:softprob",    
          "num_class" = 3,    
          "eval_metric" = "mlogloss",    
          "nthread" = 8,   
          "max_depth" = 16,   
          "eta" = 0.3,    
          "gamma" = 0,    
          "subsample" = 1,   
          "colsample_bytree" = 1,  
          "min_child_weight" = 12)

model <- xgboost(param=param, data=df, label=y, nrounds=20)

这会返回一个错误

Error in xgb.iter.update(bst$handle, dtrain, i - 1, obj) : 
SoftmaxMultiClassObj: label must be in [0, num_class), num_class=3 but found 3 in label

如果我将 num_class 更改为 2，我会得到同样的错误.如果我将 num_class 增加到 4，那么模型会运行，但我会得到 600 个预测概率，这对于 4 个类是有意义的.

If I change the num_class to 2 I get the same error. If I increase the num_class to 4 then the model runs, but I get 600 predicted probabilities back, which makes sense for 4 classes.

我不确定我是否犯了错误，或者我是否没有理解 xgboost 的工作原理.任何帮助，将不胜感激.

I'm not sure if I'm making an error or whether I'm failing to understand how xgboost works. Any help would be appreciated.

推荐答案

label must be in [0, num_class)在您的脚本中，在 model <-...

label must be in [0, num_class) in your script add y<-y-1 before model <-...

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