Running examples in ‘alookr-Ex.R’ failed
The error most likely occurred in:

> ### Name: run_models
> ### Title: Fit binary classification model
> ### Aliases: run_models
> 
> ### ** Examples
> 
> library(dplyr)

Attaching package: ‘dplyr’

The following object is masked from ‘package:randomForest’:

    combine

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

> 
> # Divide the train data set and the test data set.
> sb <- rpart::kyphosis %>%
+   split_by(Kyphosis)
> 
> # Extract the train data set from original data set.
> train <- sb %>%
+   extract_set(set = "train")
> 
> # Extract the test data set from original data set.
> test <- sb %>%
+   extract_set(set = "test")
> 
> # Sampling for unbalanced data set using SMOTE(synthetic minority over-sampling technique).
> train <- sb %>%
+   sampling_target(seed = 1234L, method = "ubSMOTE")
> 
> # Cleaning the set.
> train <- train %>%
+   cleanse
── Checking unique value ─────────────────────────── unique value is one ──
No variables that unique value is one.

── Checking unique rate ─────────────────────────────── high unique rate ──
No variables that high unique rate.

── Checking character variables ─────────────────────── categorical data ──
No character variables.

> 
> # Run the model fitting.
> result <- run_models(.data = train, target = "Kyphosis", positive = "present")
> result
# A tibble: 7 × 7
  step     model_id     target   is_factor positive negative fitted_model
  <chr>    <chr>        <chr>    <lgl>     <chr>    <chr>    <list>      
1 1.Fitted logistic     Kyphosis TRUE      present  absent   <glm>       
2 1.Fitted rpart        Kyphosis TRUE      present  absent   <rpart>     
3 1.Fitted ctree        Kyphosis TRUE      present  absent   <BinaryTr>  
4 1.Fitted randomForest Kyphosis TRUE      present  absent   <rndmFrs.>  
5 1.Fitted ranger       Kyphosis TRUE      present  absent   <ranger>    
6 1.Fitted xgboost      Kyphosis TRUE      present  absent   <xgboost>   
7 1.Fitted lasso        Kyphosis TRUE      present  absent   <lognet>    
> 
> # Run the several kinds model fitting by dplyr
> train %>%
+   run_models(target = "Kyphosis", positive = "present")

Execution halted