definitions:
  datasets:
    my_dataset:
      format: AIRR
      params:
        path: 100_receptors.tsv # path to the receptors file relative to the working directory where immuneML is executed
        is_repertoire: false
        paired: true
        receptor_chains: TRA_TRB
        metadata_column_mapping:
          binder: binder
  encodings:
    my_encoding:
      KmerFrequency:
        k: 3
    my_second_encoding:
      KmerFrequency:
        k: 4
  ml_methods:
    my_ml_method:
      LogisticRegression:
        C: [0.01, 0.1, 1, 10, 100]
      model_selection_cv: True
      model_selection_n_folds: 3
  reports:
    my_coefficients_report:
      Coefficients:
        n_largest: [5]
    my_performance_report: MLSettingsPerformance
instructions:
  my_instruction:
    type: TrainMLModel
    dataset: my_dataset
    labels: [binder]
    settings: 
      - encoding: my_encoding
        ml_method: my_ml_method
      - encoding: my_second_encoding
        ml_method: my_ml_method
    optimization_metric: balanced_accuracy
    selection:
      split_strategy: random
      split_count: 1
      training_percentage: 0.7 
    assessment:
      split_strategy: k_fold
      split_count: 3
      reports:
        models: [my_coefficients_report]
    reports: [my_performance_report] 
