用xgboost实现随机森林
时间: 2023-11-27 11:46:52 浏览: 28
使用xgboost实现随机森林的步骤如下:
1.导入所需的库和数据集:
```R
library(xgboost)
data(agaricus.train, package='xgboost')
data(agaricus.test, package='xgboost')
train <- agaricus.train
test <- agaricus.test
```
2.将数据集转换为DMatrix格式:
```R
dtrain <- xgb.DMatrix(data = train$data, label = train$label)
dtest <- xgb.DMatrix(data = test$data, label = test$label)
```
3.设置xgboost参数:
```R
params <- list(
booster = "gbtree",
objective = "binary:logistic",
eval_metric = "error",
num_round = 10,
max_depth = 6,
subsample = 0.8,
colsample_bytree = 0.8
)
```
4.训练模型:
```R
model <- xgb.train(
params = params,
data = dtrain,
nrounds = 10,
watchlist = list(train = dtrain, test = dtest),
print_every_n = 1,
early_stopping_rounds = 3
)
```
5.使用训练好的模型进行预测:
```R
pred <- predict(model, dtest)
```