def __init__()

in tensorflow_decision_forests/keras/wrappers_pre_generated.py [0:0]

• 123 lines of code
• 2 McCabe index (conditional complexity)

  def __init__(self,
               task: Optional[TaskType] = core.Task.CLASSIFICATION,
               features: Optional[List[core.FeatureUsage]] = None,
               exclude_non_specified_features: Optional[bool] = False,
               preprocessing: Optional["tf.keras.models.Functional"] = None,
               postprocessing: Optional["tf.keras.models.Functional"] = None,
               ranking_group: Optional[str] = None,
               uplift_treatment: Optional[str] = None,
               temp_directory: Optional[str] = None,
               verbose: int = 1,
               hyperparameter_template: Optional[str] = None,
               advanced_arguments: Optional[AdvancedArguments] = None,
               num_threads: Optional[int] = None,
               name: Optional[str] = None,
               max_vocab_count: Optional[int] = 2000,
               try_resume_training: Optional[bool] = True,
               check_dataset: Optional[bool] = True,
               allow_na_conditions: Optional[bool] = False,
               categorical_algorithm: Optional[str] = "CART",
               categorical_set_split_greedy_sampling: Optional[float] = 0.1,
               categorical_set_split_max_num_items: Optional[int] = -1,
               categorical_set_split_min_item_frequency: Optional[int] = 1,
               growing_strategy: Optional[str] = "LOCAL",
               honest: Optional[bool] = False,
               in_split_min_examples_check: Optional[bool] = True,
               keep_non_leaf_label_distribution: Optional[bool] = True,
               max_depth: Optional[int] = 16,
               max_num_nodes: Optional[int] = None,
               maximum_model_size_in_memory_in_bytes: Optional[float] = -1.0,
               maximum_training_duration_seconds: Optional[float] = -1.0,
               min_examples: Optional[int] = 5,
               missing_value_policy: Optional[str] = "GLOBAL_IMPUTATION",
               num_candidate_attributes: Optional[int] = 0,
               num_candidate_attributes_ratio: Optional[float] = -1.0,
               random_seed: Optional[int] = 123456,
               sorting_strategy: Optional[str] = "PRESORT",
               sparse_oblique_normalization: Optional[str] = None,
               sparse_oblique_num_projections_exponent: Optional[float] = None,
               sparse_oblique_projection_density_factor: Optional[float] = None,
               sparse_oblique_weights: Optional[str] = None,
               split_axis: Optional[str] = "AXIS_ALIGNED",
               uplift_min_examples_in_treatment: Optional[int] = 5,
               uplift_split_score: Optional[str] = "KULLBACK_LEIBLER",
               validation_ratio: Optional[float] = 0.1,
               explicit_args: Optional[Set[str]] = None):

    learner_params = {
        "allow_na_conditions":
            allow_na_conditions,
        "categorical_algorithm":
            categorical_algorithm,
        "categorical_set_split_greedy_sampling":
            categorical_set_split_greedy_sampling,
        "categorical_set_split_max_num_items":
            categorical_set_split_max_num_items,
        "categorical_set_split_min_item_frequency":
            categorical_set_split_min_item_frequency,
        "growing_strategy":
            growing_strategy,
        "honest":
            honest,
        "in_split_min_examples_check":
            in_split_min_examples_check,
        "keep_non_leaf_label_distribution":
            keep_non_leaf_label_distribution,
        "max_depth":
            max_depth,
        "max_num_nodes":
            max_num_nodes,
        "maximum_model_size_in_memory_in_bytes":
            maximum_model_size_in_memory_in_bytes,
        "maximum_training_duration_seconds":
            maximum_training_duration_seconds,
        "min_examples":
            min_examples,
        "missing_value_policy":
            missing_value_policy,
        "num_candidate_attributes":
            num_candidate_attributes,
        "num_candidate_attributes_ratio":
            num_candidate_attributes_ratio,
        "random_seed":
            random_seed,
        "sorting_strategy":
            sorting_strategy,
        "sparse_oblique_normalization":
            sparse_oblique_normalization,
        "sparse_oblique_num_projections_exponent":
            sparse_oblique_num_projections_exponent,
        "sparse_oblique_projection_density_factor":
            sparse_oblique_projection_density_factor,
        "sparse_oblique_weights":
            sparse_oblique_weights,
        "split_axis":
            split_axis,
        "uplift_min_examples_in_treatment":
            uplift_min_examples_in_treatment,
        "uplift_split_score":
            uplift_split_score,
        "validation_ratio":
            validation_ratio,
    }

    if hyperparameter_template is not None:
      learner_params = core._apply_hp_template(
          learner_params, hyperparameter_template,
          self.predefined_hyperparameters(), explicit_args)

    super(CartModel, self).__init__(
        task=task,
        learner="CART",
        learner_params=learner_params,
        features=features,
        exclude_non_specified_features=exclude_non_specified_features,
        preprocessing=preprocessing,
        postprocessing=postprocessing,
        ranking_group=ranking_group,
        uplift_treatment=uplift_treatment,
        temp_directory=temp_directory,
        verbose=verbose,
        advanced_arguments=advanced_arguments,
        num_threads=num_threads,
        name=name,
        max_vocab_count=max_vocab_count,
        try_resume_training=try_resume_training,
        check_dataset=check_dataset)