如何在R中为xgboost创建混淆矩阵

install.packages("xgboost")
install.packages("caret")

library(xgboost)
library(caret)

# 定义xgboost参数
params <- list(
  objective = "binary:logistic",
  eval_metric = "logloss"
)

# 训练xgboost模型
xgb_model <- xgboost(data = as.matrix(train_data[, -1]), 
                     label = train_data$label, 
                     params = params, 
                     nrounds = 100, 
                     verbose = 0)

# 预测测试集
predictions <- predict(xgb_model, as.matrix(test_data[, -1]))

# 将预测结果转换为二分类
binary_predictions <- ifelse(predictions > 0.5, 1, 0)

# 创建混淆矩阵
confusion_matrix <- confusionMatrix(data = binary_predictions, 
                                    reference = test_data$label)

print(confusion_matrix)