(config)
return pipeline
Create a pipeline from a config file.

    takes a config dict as input and return the coresponding pipeline.

    Parameters
    ----------
    config : Dict.
        Dict containing the config parameters.

    Returns
    -------
    pipeline : Pipeline
        sklearn Pipeline
Create a pipeline from a config file.
Create a pipeline from a config file .
def create_pipeline_from_config(config):
    """Create a pipeline from a config file.

    takes a config dict as input and return the coresponding pipeline.

    Parameters
    ----------
    config : Dict.
        Dict containing the config parameters.

    Returns
    -------
    pipeline : Pipeline
        sklearn Pipeline

    """
    components = []

    for component in config:
        # load the package
        mod = __import__(component["from"], fromlist=[component["name"]])
        # create the instance
        if "parameters" in component.keys():
            params = component["parameters"]
        else:
            params = {}
        instance = getattr(mod, component["name"])(**params)
        components.append(instance)

    pipeline = make_pipeline(*components)
    return pipeline
def create_pipeline_from_config ( config ) : components = [ ] for component in config : # load the package mod = __import__ ( component [ "from" ] , fromlist = [ component [ "name" ] ] ) # create the instance if "parameters" in component . keys ( ) : params = component [ "parameters" ] else : params = { } instance = getattr ( mod , component [ "name" ] ) ( * * params ) components . append ( instance ) pipeline = make_pipeline ( * components ) return pipeline