class_docstr: A data interface for public data. This class is an interface to DiCE explainers
  and contains methods to transform user-fed raw data into the format a DiCE explainer
  requires, and vice versa.
docstr: Validate and set the dictionary of precision for continuous features.
code: def _validate_and_set_continuous_features_precision(self, params):
      """Validate and set the dictionary of precision for continuous features."""
      if "continuous_features_precision" in params:
          self.continuous_features_precision = params[
              "continuous_features_precision"
          ]
  
          if not hasattr(self, "feature_names"):
              raise SystemException(
                  "Feature names not correctly set in public data interface"
              )
  
          for (
              continuous_features_precision_feature_name
          ) in self.continuous_features_precision:
              if (
                  continuous_features_precision_feature_name
                  not in self.feature_names
              ):
                  raise UserConfigValidationException(
                      "continuous_features_precision contains some feature names which are not part of columns in dataframe"
                  )
      else:
          self.continuous_features_precision = None
  
imports: import logging
  from collections import defaultdict
  import numpy
  import pandas
  from raiutils.exceptions import UserConfigValidationException
  from sklearn.preprocessing import LabelEncoder
  from dice_ml.data_interfaces.base_data_interface import _BaseData
  from dice_ml.utils.exception import SystemException
label_desc: Use image node_id 4 for calling the PublicData obj's underlying member method code with example usage: obj._validate_and_set_continuous_features_precision(params) without return types