Running examples in 'healthcareai-Ex.R' failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: evaluate
> ### Title: Get model performance metrics
> ### Aliases: evaluate evaluate.predicted_df evaluate.model_list
> 
> ### ** Examples
> 
> models <- machine_learn(pima_diabetes[1:40, ],
+                        patient_id,
+                        outcome = diabetes,
+                        models = c("XGB", "RF"),
+                        tune = FALSE,
+                        n_folds = 3)
Training new data prep recipe...

Variable(s) ignored in prep_data won't be used to tune models: patient_id
Error in setup_training(d, rlang::enquo(outcome), model_class, models,  : 
  All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
Calls: machine_learn -> flash_models -> setup_training
Execution halted
Running 'testthat-1.R' [0s/0s]
  Running 'testthat-2.R' [0s/0s]
  Running 'testthat-3.R' [0s/1s]
  Running 'testthat-4.R' [0s/0s]
  Running 'testthat-5.R' [7s/10s]
Running the tests in 'tests/testthat-5.R' failed.
Complete output:
  > if (!identical(Sys.getenv("NOT_CRAN"), "true")) {
  +   library(testthat)
  +   library(healthcareai)
  +   Sys.setenv("R_TESTS" = "")
  +   test_check("healthcareai", filter = "cran_only")
  + }
  healthcareai version 2.5.1
  Please visit https://docs.healthcare.ai for full documentation and vignettes. Join the community at https://healthcare-ai.slack.com
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  
  == Failed tests ================================================================
  -- Error ('test-cran_only.R:4'): the fundamentals work -------------------------
  Error in `setup_training(d, rlang::enquo(outcome), model_class, models, 
      metric, positive_class, n_folds)`: All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
  Backtrace:
      x
   1. \-healthcareai::machine_learn(...) at test-cran_only.R:4:2
   2.   \-healthcareai::flash_models(...)
   3.     \-healthcareai:::setup_training(...)
  
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  Error: Test failures
  Execution halted
Running examples in ‘healthcareai-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: evaluate
> ### Title: Get model performance metrics
> ### Aliases: evaluate evaluate.predicted_df evaluate.model_list
> 
> ### ** Examples
> 
> models <- machine_learn(pima_diabetes[1:40, ],
+                        patient_id,
+                        outcome = diabetes,
+                        models = c("XGB", "RF"),
+                        tune = FALSE,
+                        n_folds = 3)
Training new data prep recipe...

Variable(s) ignored in prep_data won't be used to tune models: patient_id
Error in setup_training(d, rlang::enquo(outcome), model_class, models,  : 
  All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
Calls: machine_learn -> flash_models -> setup_training
Execution halted
Running ‘testthat-1.R’ [0s/0s]
  Running ‘testthat-2.R’ [0s/1s]
  Running ‘testthat-3.R’ [0s/1s]
  Running ‘testthat-4.R’ [0s/1s]
  Running ‘testthat-5.R’ [5s/8s]
Running the tests in ‘tests/testthat-5.R’ failed.
Complete output:
  > if (!identical(Sys.getenv("NOT_CRAN"), "true")) {
  +   library(testthat)
  +   library(healthcareai)
  +   Sys.setenv("R_TESTS" = "")
  +   test_check("healthcareai", filter = "cran_only")
  + }
  healthcareai version 2.5.1
  Please visit https://docs.healthcare.ai for full documentation and vignettes. Join the community at https://healthcare-ai.slack.com
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-cran_only.R:4'): the fundamentals work ─────────────────────────
  Error in `setup_training(d, rlang::enquo(outcome), model_class, models, 
      metric, positive_class, n_folds)`: All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
  Backtrace:
      ▆
   1. └─healthcareai::machine_learn(...) at test-cran_only.R:4:2
   2.   └─healthcareai::flash_models(...)
   3.     └─healthcareai:::setup_training(...)
  
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  Error: Test failures
  Execution halted
Running examples in ‘healthcareai-Ex.R’ failed
The error most likely occurred in:

> ### Name: evaluate
> ### Title: Get model performance metrics
> ### Aliases: evaluate evaluate.predicted_df evaluate.model_list
> 
> ### ** Examples
> 
> models <- machine_learn(pima_diabetes[1:40, ],
+                        patient_id,
+                        outcome = diabetes,
+                        models = c("XGB", "RF"),
+                        tune = FALSE,
+                        n_folds = 3)
Training new data prep recipe...

Variable(s) ignored in prep_data won't be used to tune models: patient_id
Error in setup_training(d, rlang::enquo(outcome), model_class, models,  : 
  All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
Calls: machine_learn -> flash_models -> setup_training
Execution halted
Running ‘testthat-1.R’
  Running ‘testthat-2.R’
  Running ‘testthat-3.R’
  Running ‘testthat-4.R’
  Running ‘testthat-5.R’ [9s/13s]
Running the tests in ‘tests/testthat-5.R’ failed.
Complete output:
  > if (!identical(Sys.getenv("NOT_CRAN"), "true")) {
  +   library(testthat)
  +   library(healthcareai)
  +   Sys.setenv("R_TESTS" = "")
  +   test_check("healthcareai", filter = "cran_only")
  + }
  healthcareai version 2.5.1
  Please visit https://docs.healthcare.ai for full documentation and vignettes. Join the community at https://healthcare-ai.slack.com
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-cran_only.R:4'): the fundamentals work ─────────────────────────
  Error in `setup_training(d, rlang::enquo(outcome), model_class, models, 
      metric, positive_class, n_folds)`: All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
  Backtrace:
      ▆
   1. └─healthcareai::machine_learn(...) at test-cran_only.R:4:2
   2.   └─healthcareai::flash_models(...)
   3.     └─healthcareai:::setup_training(...)
  
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  Error: Test failures
  Execution halted
Running examples in ‘healthcareai-Ex.R’ failed
The error most likely occurred in:

> ### Name: evaluate
> ### Title: Get model performance metrics
> ### Aliases: evaluate evaluate.predicted_df evaluate.model_list
> 
> ### ** Examples
> 
> models <- machine_learn(pima_diabetes[1:40, ],
+                        patient_id,
+                        outcome = diabetes,
+                        models = c("XGB", "RF"),
+                        tune = FALSE,
+                        n_folds = 3)
Training new data prep recipe...

Variable(s) ignored in prep_data won't be used to tune models: patient_id
Error in setup_training(d, rlang::enquo(outcome), model_class, models,  : 
  All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
Calls: machine_learn -> flash_models -> setup_training
Execution halted
Running ‘testthat-1.R’
  Running ‘testthat-2.R’
  Running ‘testthat-3.R’
  Running ‘testthat-4.R’
  Running ‘testthat-5.R’ [9s/11s]
Running the tests in ‘tests/testthat-5.R’ failed.
Complete output:
  > if (!identical(Sys.getenv("NOT_CRAN"), "true")) {
  +   library(testthat)
  +   library(healthcareai)
  +   Sys.setenv("R_TESTS" = "")
  +   test_check("healthcareai", filter = "cran_only")
  + }
  healthcareai version 2.5.1
  Please visit https://docs.healthcare.ai for full documentation and vignettes. Join the community at https://healthcare-ai.slack.com
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-cran_only.R:4'): the fundamentals work ─────────────────────────
  Error in `setup_training(d, rlang::enquo(outcome), model_class, models, 
      metric, positive_class, n_folds)`: All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
  Backtrace:
      ▆
   1. └─healthcareai::machine_learn(...) at test-cran_only.R:4:2
   2.   └─healthcareai::flash_models(...)
   3.     └─healthcareai:::setup_training(...)
  
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  Error: Test failures
  Execution halted
Running examples in 'healthcareai-Ex.R' failed
The error most likely occurred in:

> ### Name: evaluate
> ### Title: Get model performance metrics
> ### Aliases: evaluate evaluate.predicted_df evaluate.model_list
> 
> ### ** Examples
> 
> models <- machine_learn(pima_diabetes[1:40, ],
+                        patient_id,
+                        outcome = diabetes,
+                        models = c("XGB", "RF"),
+                        tune = FALSE,
+                        n_folds = 3)
Training new data prep recipe...

Variable(s) ignored in prep_data won't be used to tune models: patient_id
Error in setup_training(d, rlang::enquo(outcome), model_class, models,  : 
  All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
Calls: machine_learn -> flash_models -> setup_training
Execution halted
Running 'testthat-1.R' [0s]
  Running 'testthat-2.R' [0s]
  Running 'testthat-3.R' [0s]
  Running 'testthat-4.R' [0s]
  Running 'testthat-5.R' [8s]
Running the tests in 'tests/testthat-5.R' failed.
Complete output:
  > if (!identical(Sys.getenv("NOT_CRAN"), "true")) {
  +   library(testthat)
  +   library(healthcareai)
  +   Sys.setenv("R_TESTS" = "")
  +   test_check("healthcareai", filter = "cran_only")
  + }
  healthcareai version 2.5.1
  Please visit https://docs.healthcare.ai for full documentation and vignettes. Join the community at https://healthcare-ai.slack.com
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-cran_only.R:4'): the fundamentals work ─────────────────────────
  Error in `setup_training(d, rlang::enquo(outcome), model_class, models, 
      metric, positive_class, n_folds)`: All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
  Backtrace:
      ▆
   1. └─healthcareai::machine_learn(...) at test-cran_only.R:4:2
   2.   └─healthcareai::flash_models(...)
   3.     └─healthcareai:::setup_training(...)
  
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  Error: Test failures
  Execution halted
Running examples in ‘healthcareai-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: evaluate
> ### Title: Get model performance metrics
> ### Aliases: evaluate evaluate.predicted_df evaluate.model_list
> 
> ### ** Examples
> 
> models <- machine_learn(pima_diabetes[1:40, ],
+                        patient_id,
+                        outcome = diabetes,
+                        models = c("XGB", "RF"),
+                        tune = FALSE,
+                        n_folds = 3)
Training new data prep recipe...

Variable(s) ignored in prep_data won't be used to tune models: patient_id
Error in setup_training(d, rlang::enquo(outcome), model_class, models,  : 
  All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
Calls: machine_learn -> flash_models -> setup_training
Execution halted
Running ‘testthat-1.R’ [0s/0s]
  Running ‘testthat-2.R’ [0s/1s]
  Running ‘testthat-3.R’ [0s/1s]
  Running ‘testthat-4.R’ [0s/0s]
  Running ‘testthat-5.R’ [7s/9s]
Running the tests in ‘tests/testthat-5.R’ failed.
Complete output:
  > if (!identical(Sys.getenv("NOT_CRAN"), "true")) {
  +   library(testthat)
  +   library(healthcareai)
  +   Sys.setenv("R_TESTS" = "")
  +   test_check("healthcareai", filter = "cran_only")
  + }
  healthcareai version 2.5.1
  Please visit https://docs.healthcare.ai for full documentation and vignettes. Join the community at https://healthcare-ai.slack.com
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-cran_only.R:4'): the fundamentals work ─────────────────────────
  Error in `setup_training(d, rlang::enquo(outcome), model_class, models, 
      metric, positive_class, n_folds)`: All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
  Backtrace:
      ▆
   1. └─healthcareai::machine_learn(...) at test-cran_only.R:4:2
   2.   └─healthcareai::flash_models(...)
   3.     └─healthcareai:::setup_training(...)
  
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  Error: Test failures
  Execution halted
Running examples in ‘healthcareai-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: evaluate
> ### Title: Get model performance metrics
> ### Aliases: evaluate evaluate.predicted_df evaluate.model_list
> 
> ### ** Examples
> 
> models <- machine_learn(pima_diabetes[1:40, ],
+                        patient_id,
+                        outcome = diabetes,
+                        models = c("XGB", "RF"),
+                        tune = FALSE,
+                        n_folds = 3)
Training new data prep recipe...

Variable(s) ignored in prep_data won't be used to tune models: patient_id
Error in setup_training(d, rlang::enquo(outcome), model_class, models,  : 
  All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
Calls: machine_learn -> flash_models -> setup_training
Execution halted
Running ‘testthat-1.R’ [0s/0s]
  Running ‘testthat-2.R’ [0s/1s]
  Running ‘testthat-3.R’ [0s/1s]
  Running ‘testthat-4.R’ [0s/1s]
  Running ‘testthat-5.R’ [7s/9s]
Running the tests in ‘tests/testthat-5.R’ failed.
Complete output:
  > if (!identical(Sys.getenv("NOT_CRAN"), "true")) {
  +   library(testthat)
  +   library(healthcareai)
  +   Sys.setenv("R_TESTS" = "")
  +   test_check("healthcareai", filter = "cran_only")
  + }
  healthcareai version 2.5.1
  Please visit https://docs.healthcare.ai for full documentation and vignettes. Join the community at https://healthcare-ai.slack.com
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-cran_only.R:4'): the fundamentals work ─────────────────────────
  Error in `setup_training(d, rlang::enquo(outcome), model_class, models, 
      metric, positive_class, n_folds)`: All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
  Backtrace:
      ▆
   1. └─healthcareai::machine_learn(...) at test-cran_only.R:4:2
   2.   └─healthcareai::flash_models(...)
   3.     └─healthcareai:::setup_training(...)
  
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  Error: Test failures
  Execution halted
Running examples in 'healthcareai-Ex.R' failed
The error most likely occurred in:

> ### Name: evaluate
> ### Title: Get model performance metrics
> ### Aliases: evaluate evaluate.predicted_df evaluate.model_list
> 
> ### ** Examples
> 
> models <- machine_learn(pima_diabetes[1:40, ],
+                        patient_id,
+                        outcome = diabetes,
+                        models = c("XGB", "RF"),
+                        tune = FALSE,
+                        n_folds = 3)
Training new data prep recipe...

Variable(s) ignored in prep_data won't be used to tune models: patient_id
Error in setup_training(d, rlang::enquo(outcome), model_class, models,  : 
  All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
Calls: machine_learn -> flash_models -> setup_training
Execution halted
Running 'testthat-1.R' [0s]
  Running 'testthat-2.R' [0s]
  Running 'testthat-3.R' [0s]
  Running 'testthat-4.R' [0s]
  Running 'testthat-5.R' [7s]
Running the tests in 'tests/testthat-5.R' failed.
Complete output:
  > if (!identical(Sys.getenv("NOT_CRAN"), "true")) {
  +   library(testthat)
  +   library(healthcareai)
  +   Sys.setenv("R_TESTS" = "")
  +   test_check("healthcareai", filter = "cran_only")
  + }
  healthcareai version 2.5.1
  Please visit https://docs.healthcare.ai for full documentation and vignettes. Join the community at https://healthcare-ai.slack.com
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-cran_only.R:4'): the fundamentals work ─────────────────────────
  Error in `setup_training(d, rlang::enquo(outcome), model_class, models, 
      metric, positive_class, n_folds)`: All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
  Backtrace:
      ▆
   1. └─healthcareai::machine_learn(...) at test-cran_only.R:4:2
   2.   └─healthcareai::flash_models(...)
   3.     └─healthcareai:::setup_training(...)
  
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  Error: Test failures
  Execution halted
Running examples in 'healthcareai-Ex.R' failed
The error most likely occurred in:

> ### Name: evaluate
> ### Title: Get model performance metrics
> ### Aliases: evaluate evaluate.predicted_df evaluate.model_list
> 
> ### ** Examples
> 
> models <- machine_learn(pima_diabetes[1:40, ],
+                        patient_id,
+                        outcome = diabetes,
+                        models = c("XGB", "RF"),
+                        tune = FALSE,
+                        n_folds = 3)
Training new data prep recipe...

Variable(s) ignored in prep_data won't be used to tune models: patient_id
Error in setup_training(d, rlang::enquo(outcome), model_class, models,  : 
  All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
Calls: machine_learn -> flash_models -> setup_training
Execution halted
Running 'testthat-1.R' [0s]
  Running 'testthat-2.R' [0s]
  Running 'testthat-3.R' [0s]
  Running 'testthat-4.R' [0s]
  Running 'testthat-5.R' [7s]
Running the tests in 'tests/testthat-5.R' failed.
Complete output:
  > if (!identical(Sys.getenv("NOT_CRAN"), "true")) {
  +   library(testthat)
  +   library(healthcareai)
  +   Sys.setenv("R_TESTS" = "")
  +   test_check("healthcareai", filter = "cran_only")
  + }
  healthcareai version 2.5.1
  Please visit https://docs.healthcare.ai for full documentation and vignettes. Join the community at https://healthcare-ai.slack.com
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  
  == Failed tests ================================================================
  -- Error ('test-cran_only.R:4'): the fundamentals work -------------------------
  Error in `setup_training(d, rlang::enquo(outcome), model_class, models, 
      metric, positive_class, n_folds)`: All predictors must be numeric, but the following variables are not numeric. Consider using prep_data to get data ready for model training: weight_class
  Backtrace:
      x
   1. \-healthcareai::machine_learn(...) at test-cran_only.R:4:2
   2.   \-healthcareai::flash_models(...)
   3.     \-healthcareai:::setup_training(...)
  
  [ FAIL 1 | WARN 0 | SKIP 0 | PASS 0 ]
  Error: Test failures
  Execution halted