Predict target using a trained model.
Arguments
- data
A dataset (data.frame or tbl)
- model
A model created with
explain_*()function- name
Prefix of variable-name for prediction
Examples
data_train <- create_data_buy(seed = 1)
data_test <- create_data_buy(seed = 2)
model <- explain_tree(data_train, target = buy, out = "model")
data <- predict_target(data = data_test, model = model)
describe(data)
#> # A tibble: 15 × 8
#> variable type na na_pct unique min mean max
#> <chr> <chr> <int> <dbl> <int> <dbl> <dbl> <dbl>
#> 1 period int 0 0 1 202012 202012 202012
#> 2 buy int 0 0 2 0 0.5 1
#> 3 age int 0 0 65 20 52.7 95
#> 4 city_ind int 0 0 2 0 0.5 1
#> 5 female_ind int 0 0 2 0 0.53 1
#> 6 fixedvoice_ind int 0 0 2 0 0.1 1
#> 7 fixeddata_ind int 0 0 1 1 1 1
#> 8 fixedtv_ind int 0 0 2 0 0.4 1
#> 9 mobilevoice_ind int 0 0 2 0 0.59 1
#> 10 mobiledata_prd chr 0 0 3 NA NA NA
#> 11 bbi_speed_ind int 0 0 2 0 0.61 1
#> 12 bbi_usg_gb int 0 0 88 7 164. 100000
#> 13 hh_single int 0 0 2 0 0.33 1
#> 14 prediction_0 dbl 0 0 6 0.1 0.5 0.88
#> 15 prediction_1 dbl 0 0 6 0.12 0.5 0.9