```
library(sparklyr)
<- spark_connect("local")
sc <- copy_to(sc, iris)
tbl_iris <- sdf_random_split(tbl_iris, training = 0.5, test = 0.5)
iris_split <- iris_split$training
training <- "Sepal_Length ~ Sepal_Width + Petal_Length + Petal_Width"
reg_formula <- ml_generalized_linear_regression(training, reg_formula)
model <- ml_predict(model, iris_split$test)
tbl_predictions %>%
tbl_predictions ml_metrics_regression(Sepal_Length)
#> # A tibble: 3 × 3
#> .metric .estimator .estimate
#> <chr> <chr> <dbl>
#> 1 rmse standard 0.313
#> 2 rsq standard 0.863
#> 3 mae standard 0.249
```

# Extracts metrics from a fitted table

*R/ml_metrics.R*

## ml_metrics_regression

## Description

The function works best when passed a `tbl_spark`

created by `ml_predict()`

. The output `tbl_spark`

will contain the correct variable types and format that the given Spark model “evaluator” expects.

## Usage

```
ml_metrics_regression(
x,
truth, estimate = prediction,
metrics = c("rmse", "rsq", "mae"),
... )
```

## Arguments

Arguments | Description |
---|---|

x | A `tbl_spark` containing the estimate (prediction) and the truth (value of what actually happened) |

truth | The name of the column from `x` that contains the value of what actually happened |

estimate | The name of the column from `x` that contains the prediction. Defaults to `prediction` , since it is the default that `ml_predict()` uses. |

metrics | A character vector with the metrics to calculate. For regression models the possible values are: `rmse` (Root mean squared error), `mse` (Mean squared error),`rsq` (R squared), `mae` (Mean absolute error), and `var` (Explained variance). Defaults to: `rmse` , `rsq` , `mae` |

… | Optional arguments; currently unused. |

## Details

The `ml_metrics`

family of functions implement Spark’s `evaluate`

closer to how the `yardstick`

package works. The functions expect a table containing the truth and estimate, and return a `tibble`

with the results. The `tibble`

has the same format and variable names as the output of the `yardstick`

functions.