loss_function | R Documentation |

`loss_function()`

estimates the loss based on a loss function.

loss_function( pred, data.valid, loss.unit = c("individuals", "L2 units"), loss.fun = c("MSE", "MAE", "cross-entropy"), y, L2.unit )

`pred` |
Predictions of outcome. A numeric vector of outcome predictions. |

`data.valid` |
Test data set. A tibble of data that was not used for prediction. |

`loss.unit` |
Loss function unit. A character-valued scalar indicating
whether performance loss should be evaluated at the level of individual
respondents ( |

`loss.fun` |
Loss function. A character-valued scalar indicating whether
prediction loss should be measured by the mean squared error ( |

`y` |
Outcome variable. A character vector containing the column names of the outcome variable. |

`L2.unit` |
Geographic unit. A character scalar containing the column name
of the geographic unit in |

Returns a tibble with number of rows equal to the number of loss functions tested (defaults to 4 for cross-entropy, f1, MSE, and msfe). The number of columns is 2 where the first is called measure and contains the names of the loss-functions and the second is called value and contains the loss-function scores.

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