na.fail.default 中的随机森林错误：对象中缺少值

Question

我是运行一个RF模型，它运行大多数变量都没有错误；但是，当我包含一个变量：duration_in_program 和以下代码时：

```{r Random Forest Model}
## Run a Random Forest model
mod_rf <-
  train(left_school ~ job_title 
        + gender + 
        + marital_status + age_at_enrollment + monthly_wage + educational_qualification + cityD + educational_qualification + cityC.
        + cityB +cityA + duration_in_program, # Equation (outcome and everything else)
        data=train_data, # Training data 
        method = "ranger", # random forest (ranger is much faster than rf)
        metric = "ROC", # area under the curve
        trControl = control_conditions,
        tuneGrid = tune_mtry
  )
mod_rf

我收到以下错误：

Error in na.fail.default(list(left_welfare = c(1L, 2L, 2L, 2L, 2L, 2L, : missing values in object

Answer 1

假设 train() 来自插入符号，您可以使用 na.action 参数指定一个函数来处理 na。默认值为 na.fail。一个很常见的是 na.omit。 randomForest 库有 na.roughfix 将 "Impute Missing Values by median/mode."

mod_rf <-
  train(left_school ~ job_title 
        + gender + 
        + marital_status + age_at_enrollment + monthly_wage + educational_qualification + cityD + educational_qualification + cityC.
        + cityB +cityA + duration_in_program, # Equation (outcome and everything else)
        data=train_data, # Training data 
        method = "ranger", # random forest (ranger is much faster than rf)
        metric = "ROC", # area under the curve
        trControl = control_conditions,
        tuneGrid = tune_mtry,
        na.action = na.omit
  )
mod_rf

na.fail.default 中的随机森林错误：对象中缺少值

Random Forest Error in na.fail.default: missing values in object

machine-learning

random-forest

r-caret

feature-selection