how to calculate rmse for models in a list in r in r

To calculate the RMSE (Root Mean Squared Error) for models in a list in R, you can follow these steps:

1. Define a function to calculate the RMSE:

rmse <- function(actual, predicted) {
  sqrt(mean((actual - predicted)^2))
}
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2. Create a list of models that you want to calculate the RMSE for:

model_list <- list(model1, model2, model3)  # replace model1, model2, model3 with your actual models
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3. Iterate over the models in the list and calculate the RMSE:

rmse_list <- lapply(model_list, function(model) {
  predicted <- predict(model)  # replace 'predict' with the actual predict function of your model
  rmse(actual, predicted)  # replace 'actual' with the actual test set values
})
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The lapply function applies the provided function to each element of the model_list and returns a list of the calculated RMSE values.

Note: Make sure to replace model1, model2, model3, predict, and actual with the appropriate names or objects from your code.

This code will give you a list rmse_list containing the RMSE values for each model in the model_list.