This function is similar to `make_class_pred()`

, but is useful when you have
a large number of class probability columns and want to use `tidyselect`

helpers. It appends the new `class_pred`

vector as a column on the original
data frame.

append_class_pred(
.data,
...,
levels,
ordered = FALSE,
min_prob = 1/length(levels),
name = ".class_pred"
)

## Arguments

.data |
A data frame or tibble. |

... |
One or more unquoted expressions separated by commas
to capture the columns of `.data` containing the class
probabilities. You can treat variable names like they are
positions, so you can use expressions like `x:y` to select ranges
of variables or use selector functions to choose which columns.
For `make_class_pred` , the columns for all class probabilities
should be selected (in the same order as the `levels` object).
For `two_class_pred` , a vector of class probabilities should be
selected. |

levels |
A character vector of class levels. The length should be the
same as the number of selections made through `...` , or length `2`
for `make_two_class_pred()` . |

ordered |
A single logical to determine if the levels should be regarded
as ordered (in the order given). This results in a `class_pred` object
that is flagged as ordered. |

min_prob |
A single numeric value. If any probabilities are less than
this value (by row), the row is marked as *equivocal*. |

name |
A single character value for the name of the appended
`class_pred` column. |

## Value

`.data`

with an extra `class_pred`

column appended onto it.

## Examples

#>
#> Attaching package: ‘dplyr’

#> The following objects are masked from ‘package:stats’:
#>
#> filter, lag

#> The following objects are masked from ‘package:base’:
#>
#> intersect, setdiff, setequal, union

#> # A tibble: 110 x 5
#> Species .pred_bobcat .pred_coyote .pred_gray_fox .class_pred
#> <fct> <dbl> <dbl> <dbl> <clss_prd>
#> 1 gray_fox 0.0976 0.0530 0.849 gray_fox
#> 2 gray_fox 0.155 0.139 0.706 gray_fox
#> 3 bobcat 0.501 0.0880 0.411 bobcat
#> 4 gray_fox 0.256 0 0.744 gray_fox
#> 5 gray_fox 0.463 0.287 0.250 [EQ]
#> 6 bobcat 0.811 0 0.189 bobcat
#> 7 bobcat 0.911 0.0888 0 bobcat
#> 8 bobcat 0.898 0.0517 0.0500 bobcat
#> 9 bobcat 0.771 0.229 0 bobcat
#> 10 bobcat 0.623 0.325 0.0517 bobcat
#> # … with 100 more rows

#> # A tibble: 110 x 5
#> Species .pred_bobcat .pred_coyote .pred_gray_fox .class_pred
#> <fct> <dbl> <dbl> <dbl> <clss_prd>
#> 1 gray_fox 0.0976 0.0530 0.849 gray_fox
#> 2 gray_fox 0.155 0.139 0.706 gray_fox
#> 3 bobcat 0.501 0.0880 0.411 bobcat
#> 4 gray_fox 0.256 0 0.744 gray_fox
#> 5 gray_fox 0.463 0.287 0.250 [EQ]
#> 6 bobcat 0.811 0 0.189 bobcat
#> 7 bobcat 0.911 0.0888 0 bobcat
#> 8 bobcat 0.898 0.0517 0.0500 bobcat
#> 9 bobcat 0.771 0.229 0 bobcat
#> 10 bobcat 0.623 0.325 0.0517 bobcat
#> # … with 100 more rows