feyn.insights

class FeatureImportanceTable

def __init__(
    model: feyn._model.Model,
    dataframe: Iterable,
    bg_data: Optional[Iterable] = None,
    max_ref_samples: Optional[int] = 100,
    max_rows: Optional[int] = 10,
    style: Optional[str] = 'bar',
    only_color_features: Optional[bool] = True
) -> FeatureImportanceTable

method FeatureImportanceTable.write_table

def write_table(
    self
)

class KernelShap

def __init__(
    model,
    bg_data,
    max_samples=10000
) -> KernelShap

Calculates the SHAP values for a given feyn.Model with your provided instances

method KernelShap.SHAP

def SHAP(
    self,
    instances
)

Calculates the SHAP values for the provided instances

Arguments:
    instances {dict(str, np.array) or pd.DataFrame} -- One or more instances to get SHAP values for.

Returns:
    [np.array] -- A numpy array (matrix) containing feature importances for your instances