r - 具有自定义成本函数的插入符号模型

Question

我想训练一个具有案例加权误差函数的 Elastic Net 分类器。该函数需要接受一个额外的参数weights，该参数允许不同的观察值在计算性能误差时携带不同的权重。这可以在插入符号中做到吗？

# Weighted RMSE function with weights argument.
weighted_rmse <- function(prediction, target, weights) {
  sum(abs(prediction - target)) * weights
}

# Example data.
trainX <- iris[1:100, 1:4]
trainOutcome <- as.numeric(iris$Species[1:100])

fit <- train(
  x = trainX, y = trainOutcome,
  method = "glmnet",
  trControl = trainControl(
    method = "loocv",
    selectionFunction = "oneSE",
    summaryFunction = twoClassSummary # <- replace with something like weighted_rsme()
  )
)

标签： rr-caret