gcms_ensembles.md
In caretSDM: Build Species Distribution Modeling using 'caret'

gcms_ensembles/names

Code
  i
Output
              caretSDM           
  ...............................
  Class                         : input_sdm
  --------  Occurrences  --------
  Species Names                 : Araucaria angustifolia 
  Number of presences           : 420 
  Pseudoabsence methods         :
      Method to obtain PAs      : random 
      Number of PA sets         : 2 
      Number of PAs in each set : 420 
  --------  Predictors  ---------
  Number of Predictors          : 2 
  Predictors Names              : bio1, bio12 
  ---------  Scenarios  ---------
  Number of Scenarios           : 5 
  Scenarios Names               : ca_ssp245_2090 ca_ssp585_2090 mi_ssp245_2090 mi_ssp585_2090 current 
  -----------  Models  ----------
  Algorithms Names              : naive_bayes 
  Variables Names               : bio1 bio12 
  Model Validation              :
      Method                    : boot 
      Number                    : 1 
      Metrics                   :
  $`Araucaria angustifolia`
           algo       ROC       TSS Sensitivity Specificity
  1 naive_bayes 0.8799581 0.4247848       0.974       0.451

  --------  Predictions  --------
  Ensembles                     :
      Scenarios                 : ca_ssp245_2090 ca_ssp585_2090 mi_ssp245_2090 mi_ssp585_2090 current _ssp245_2090 _ssp585_2090 
      Methods                   : mean_occ_prob wmean_AUC committee_avg 
  Thresholds                    :
      Method                    : threshold 
      Criteria                  : 0.8