class_docstr: A recipe for developing high-quality regression models. The recipe is designed for
  developing models using scikit-learn and frameworks that integrate with scikit-learn,
  such as the ``XGBRegressor`` API from XGBoost. The corresponding recipe
  template repository is available at https://github.com/mlflow/recipes-regression-template.
  The training recipe contains the following sequential steps:
  
  **ingest** -> **split** -> **transform** -> **train** -> **evaluate** -> **register**
  
  while the batch scoring recipe contains this set of sequential steps:
  
  **ingest_scoring** -> **predict**
  
  .. code-block:: python
      :caption: Example
  
      import os
      from mlflow.recipes import Recipe
  
      os.chdir("~/recipes-regression-template")
      regression_recipe = Recipe(profile="local")
      # Display a visual overview of the recipe graph
      regression_recipe.inspect()
      # Run the full recipe
      regression_recipe.run()
      # Display a summary of results from the 'train' step, including the trained model
      # and associated performance metrics computed from the training & validation datasets
      regression_recipe.inspect(step="train")
      # Display a summary of results from the 'evaluate' step, including model explanations
      # computed from the validation dataset and metrics computed from the test dataset
      regression_recipe.inspect(step="evaluate")
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docstr: Removes all recipe outputs from the cache, or removes the cached outputs of a particular
  recipe step if specified. After cached outputs are cleaned for a particular step, the
  step will be re-executed in its entirety the next time it is run.
  
  :param step: String name of the step to clean within the recipe. If not specified,
               cached outputs are removed for all recipe steps.
  
  .. code-block:: python
      :caption: Example
  
      import os
      from mlflow.recipes import Recipe
  
      os.chdir("~/recipes-regression-template")
      regression_recipe = Recipe(profile="local")
      # Run the 'train' step and preceding steps
      regression_recipe.run(step="train")
      # Clean the cache of the 'transform' step
      regression_recipe.clean(step="transform")
      # Run the 'split' step; outputs are still cached because 'split' precedes
      # 'transform' & 'train'
      regression_recipe.run(step="split")
      # Run the 'train' step again; the 'transform' and 'train' steps are re-executed because:
      # 1. the cache of the preceding 'transform' step was cleaned and 2. 'train' occurs after
      # 'transform'. The 'ingest' and 'split' steps are not re-executed because their outputs
      # are still cached
      regression_recipe.run(step="train")
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code: def clean(self, step: Optional[str] = None) -> None:
      """
      Removes all recipe outputs from the cache, or removes the cached outputs of a particular
      recipe step if specified. After cached outputs are cleaned for a particular step, the
      step will be re-executed in its entirety the next time it is run.
  
      :param step: String name of the step to clean within the recipe. If not specified,
                   cached outputs are removed for all recipe steps.
  
      .. code-block:: python
          :caption: Example
  
          import os
          from mlflow.recipes import Recipe
  
          os.chdir("~/recipes-regression-template")
          regression_recipe = Recipe(profile="local")
          # Run the 'train' step and preceding steps
          regression_recipe.run(step="train")
          # Clean the cache of the 'transform' step
          regression_recipe.clean(step="transform")
          # Run the 'split' step; outputs are still cached because 'split' precedes
          # 'transform' & 'train'
          regression_recipe.run(step="split")
          # Run the 'train' step again; the 'transform' and 'train' steps are re-executed because:
          # 1. the cache of the preceding 'transform' step was cleaned and 2. 'train' occurs after
          # 'transform'. The 'ingest' and 'split' steps are not re-executed because their outputs
          # are still cached
          regression_recipe.run(step="train")
      """
      super().clean(step=step)
  
file_path: mlflow/mlflow/recipes/regression/v1/recipe.py
imports: import logging
  from typing import Any, Optional
  from mlflow.recipes.recipe import BaseRecipe
  from mlflow.recipes.step import BaseStep
  from mlflow.recipes.steps.evaluate import EvaluateStep
  from mlflow.recipes.steps.ingest import IngestScoringStep, IngestStep
  from mlflow.recipes.steps.predict import PredictStep
  from mlflow.recipes.steps.register import RegisterStep
  from mlflow.recipes.steps.split import SplitStep
  from mlflow.recipes.steps.train import TrainStep
  from mlflow.recipes.steps.transform import TransformStep
label_desc: Use image node_id 5 for calling the RegressionRecipe obj's underlying member method code with example usage: obj.clean(step) without return types