Description Usage Arguments Value Author(s) Examples
The function takes the input dataframe with observed and predicted columns and computes mean absolute error, mean squared error and root mean squared error terms.
1 |
base |
input dataframe |
observed_col |
column / field name of the observed event |
predicted_col |
column / field name of the predicted event |
An object of class "fn_error" is a list containing the following components:
mean_abs_error |
mean absolute error between observed and predicted value |
mean_sq_error |
mean squared error between observed and predicted value |
root_mean_sq_error |
root mean squared error between observed and predicted value |
Arya Poddar <aryapoddar290990@gmail.com>
1 2 3 4 5 6 7 8 9 10 | data <- iris
data$Species <- as.character(data$Species)
suppressWarnings(RNGversion('3.5.0'))
set.seed(11)
data$Y <- sample(0:1,size=nrow(data),replace=TRUE)
data$Y_pred <- sample(0:1,size=nrow(data),replace=TRUE)
fn_error_list <- fn_error(base = data,observed_col = "Y",predicted_col = "Y_pred")
fn_error_list$mean_abs_error
fn_error_list$mean_sq_error
fn_error_list$root_mean_sq_error
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