R: Mean log loss for Poisson data

poisson_log_loss {yardstick} | R Documentation

## Mean log loss for Poisson data

### Description

Calculate the loss function for the Poisson distribution.

### Usage

    poisson_log_loss(data, ...)

    ## S3 method for class 'data.frame'
    poisson_log_loss(data, truth, estimate, na_rm = TRUE, ...)

    poisson_log_loss_vec(truth, estimate, na_rm = TRUE, ...)

### Arguments

`data` | A `data.frame` containing the `truth` and `estimate` columns.
`...` | Not currently used.
`truth` | The column identifier for the true counts (that is `integer`). This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For `_vec()` functions, an `integer` vector.
`estimate` | The column identifier for the predicted results (that is also `numeric`). As with `truth` this can be specified different ways but the primary method is to use an unquoted variable name. For `_vec()` functions, a `numeric` vector.
`na_rm` | A `logical` value indicating whether `NA` values should be stripped before the computation proceeds.

### Value

A `tibble` with columns `.metric`, `.estimator`, and `.estimate` and 1 row of values.

For grouped data frames, the number of rows returned will be the same as the number of groups.

For `poisson_log_loss_vec()`, a single `numeric` value (or `NA`).

### Author(s)

Max Kuhn

### See Also

Other numeric metrics: `ccc()`, `huber_loss_pseudo()`, `huber_loss()`, `iic()`, `mae()`, `mape()`, `mase()`, `mpe()`, `msd()`, `rmse()`, `rpd()`, `rpiq()`, `rsq_trad()`, `rsq()`, `smape()`

Other accuracy metrics: `ccc()`, `huber_loss_pseudo()`, `huber_loss()`, `iic()`, `mae()`, `mape()`, `mase()`, `mpe()`, `msd()`, `rmse()`, `smape()`

### Examples

    count_truth <- c(2L,   7L,   1L,   1L,   0L,  3L)
    count_pred  <- c(2.14, 5.35, 1.65, 1.56, 1.3, 2.71)
    count_results <- dplyr::tibble(count = count_truth, pred = count_pred)

    # Supply truth and predictions as bare column names
    poisson_log_loss(count_results, count, pred)

[Package yardstick version 0.0.9 Index]