task 1 failed - "The tuning parameter grid should have columns nrounds, max_depth, eta, gamma, colsample_bytree, min_child_weight, subsample"
时间: 2024-02-07 10:04:10 浏览: 26
很抱歉,我的代码示例中可能有误导之处。具体来说,您的错误提示表明您需要在调参的参数组合中包含nrounds、max_depth、eta、gamma、colsample_bytree、min_child_weight和subsample这七个参数。以下是一个更新后的代码示例:
```R
# 载入所需包
library(caret)
library(xgboost)
# 载入数据
data(iris)
x <- iris[, 1:4]
y <- iris[, 5]
# 将数据划分为训练集和测试集
trainIndex <- createDataPartition(y, p = 0.7, list = FALSE, times = 1)
x_train <- x[trainIndex, ]
x_test <- x[-trainIndex, ]
y_train <- y[trainIndex]
y_test <- y[-trainIndex]
# 建立xgbtree模型
xgb_model <- train(x = x_train, y = y_train, method = "xgbTree", trControl = trainControl(method = "cv", number = 5))
# 输出模型结果
print(xgb_model)
# 调参
tune_grid <- expand.grid(nrounds = c(50, 100, 150),
max_depth = c(3, 4, 5),
eta = c(0.1, 0.01),
gamma = c(0, 0.1),
colsample_bytree = c(0.5, 0.6, 0.7),
min_child_weight = c(1, 2),
subsample = c(0.6, 0.7, 0.8))
xgb_model_tuned <- train(x = x_train, y = y_train, method = "xgbTree", trControl = trainControl(method = "cv", number = 5), tuneGrid = tune_grid)
# 输出调参后的模型结果
print(xgb_model_tuned)
```
在这个代码示例中,我们将调参的参数组合修改为包含了nrounds、max_depth、eta、gamma、colsample_bytree、min_child_weight和subsample这七个参数。其中,我们为每个参数指定了多个可能的值。在实际应用中,您也可以根据自己的经验和问题的特点适当调整参数的范围和步长。