`[.xgb.DMatrix`(x, 0, , drop = FALSE) 中的错误：R 中未使用的参数 (drop = FALSE)

Question

我正在使用 xgboost 进行时间序列预测，他们运行 train 函数它给了我这个错误：[.xgb.DMatrix(x, 0, , drop = FALSE) 中的错误：未使用的参数 (drop = FALSE)

代码：

data <- economics %>% dplyr::select(date, unemploy)

extended_data <- data %>% 
  rbind(tibble::tibble(date = seq(from = lubridate::as_date("2015-05-01"),
                                  by = "month", length.out = 12), 
                       unemploy = rep(NA, 12)))

extended_data_mod <- extended_data %>%
  dplyr::mutate(., 
                months = lubridate::month(date),
                years = lubridate::year(date))

train <- extended_data_mod[1:nrow(data), ] # initial data

pred <- extended_data_mod[(nrow(data) + 1):nrow(extended_data), ] # extended time index

trainig <- sparse.model.matrix( ~ .-1, data = train)

x_train <- xgboost::xgb.DMatrix(as.matrix(train %>%
                                            dplyr::select(months, years)))
x_pred <- xgboost::xgb.DMatrix(as.matrix(pred %>% 
                                           dplyr::select(months, years)))

y_train <- train$unemploy


xgb_trcontrol <- caret::trainControl(
  method = "cv", 
  number = 5,
  allowParallel = TRUE, 
  verboseIter = FALSE, 
  returnData = FALSE
)

xgb_grid <- base::expand.grid(
  list(
    nrounds = c(100, 200),
    max_depth = c(10, 15, 20), # maximum depth of a tree
    colsample_bytree = seq(0.5), # subsample ratio of columns when construction each tree
    eta = 0.1, # learning rate
    gamma = 0, # minimum loss reduction
    min_child_weight = 1,  # minimum sum of instance weight (hessian) needed ina child
    subsample = 1 # subsample ratio of the training instances
  ))

xgb_model <- caret::train(
  x_train, y_train,
  trControl = xgb_trcontrol,
  tuneGrid = xgb_grid,
  method = "xgbTree",
  nthread = 1
)

我还没有发现任何其他东西，也许有些人有其他实现或如何解决这个问题？

Answer 1

同样的错误，我猜是包版本问题引起的。你能解决它吗？