cal-estimate-multinomial.md
In probably: Tools for Post-Processing Predicted Values

Multinomial estimates work - data.frame

Code
  print(sp_multi)
Message

  -- Probability Calibration 
  Method: Multinomial regression calibration
  Type: Multiclass
  Source class: Data Frame
  Data points: 110
  Truth variable: `Species`
  Estimate variables:
  `.pred_bobcat` ==> bobcat
  `.pred_coyote` ==> coyote
  `.pred_gray_fox` ==> gray_fox

Code
  print(sp_smth_multi)
Message

  -- Probability Calibration 
  Method: Generalized additive model calibration
  Type: Multiclass
  Source class: Data Frame
  Data points: 110
  Truth variable: `Species`
  Estimate variables:
  `.pred_bobcat` ==> bobcat
  `.pred_coyote` ==> coyote
  `.pred_gray_fox` ==> gray_fox

Code
  print(sl_multi_group)
Message

  -- Probability Calibration 
  Method: Multinomial regression calibration
  Type: Multiclass
  Source class: Data Frame
  Data points: 110, split in 2 groups
  Truth variable: `Species`
  Estimate variables:
  `.pred_bobcat` ==> bobcat
  `.pred_coyote` ==> coyote
  `.pred_gray_fox` ==> gray_fox

x `.by` cannot select more than one column.
i The following columns were selected:
i group1 and group2

Multinomial estimates work - tune_results

Code
  print(tl_multi)
Message

  -- Probability Calibration 
  Method: Multinomial regression calibration
  Type: Multiclass
  Source class: Tune Results
  Data points: 5,000, split in 10 groups
  Truth variable: `class`
  Estimate variables:
  `.pred_one` ==> one
  `.pred_two` ==> two
  `.pred_three` ==> three

Code
  print(tl_smth_multi)
Message

  -- Probability Calibration 
  Method: Generalized additive model calibration
  Type: Multiclass
  Source class: Tune Results
  Data points: 5,000, split in 10 groups
  Truth variable: `class`
  Estimate variables:
  `.pred_one` ==> one
  `.pred_two` ==> two
  `.pred_three` ==> three

Multinomial estimates errors - grouped_df

x This function does not work with grouped data frames.
i Apply `dplyr::ungroup()` and use the `.by` argument.

Multinomial spline switches to linear if too few unique

Code
  sl_gam <- cal_estimate_multinomial(smol_species_probs, Species, smooth = TRUE)
Condition
  Warning:
  Too few unique observations for spline-based calibrator. Setting `smooth = FALSE`.

Code
  sl_gam <- cal_estimate_multinomial(smol_by_species_probs, Species, .by = id,
    smooth = TRUE)
Condition
  Warning:
  Too few unique observations for spline-based calibrator. Setting `smooth = FALSE`.
  Warning:
  Too few unique observations for spline-based calibrator. Setting `smooth = FALSE`.