class_docstr: RIPPER (Repeated Incremental Pruning to Produce Error Reduction) is a heuristic rule induction algorithm
  based on separate-and-conquer. The explainer outputs a rule set in Disjunctive Normal Form (DNF) for a single
  target concept.
  
  References:
      .. [#ML95] `William W Cohen, "Fast Effective Rule Induction"
          Machine Learning: Proceedings of the Twelfth International Conference, 1995.
          <http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.107.2612&rep=rep1&type=pdf>
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docstr: Export rules to technical interchange format trxf from internal representation
  Returns a list of rule sets.
  
  Returns:
      list(trxf.DnfRuleSet): -- Ordered list of rulesets
docstr_tok: ["Export","rules","to","technical","interchange","format","trxf","from","internal","representation","Returns","a","list","of","rule","sets",".","Returns",":","list","(","trxf.DnfRuleSet",")",":","--","Ordered","list","of","rulesets"]
code: def explain_multiclass(self):
      """
      Export rules to technical interchange format trxf from internal representation
      Returns a list of rule sets.
  
      Returns:
          list(trxf.DnfRuleSet): -- Ordered list of rulesets
      """
      res = list()
      if len(self._rule_map.items()) == 0:
          return DnfRuleSet([], self.target_label)
      for label, rules in self._rule_map.items():
          dnf_ruleset = self._rules_to_trxf_dnf_ruleset(rules, label)
          res.append(dnf_ruleset)
      default_rule = DnfRuleSet([], self.default_label)
      res.append(default_rule)
      return res
  
imports: import logging
  import logging.config
  from collections import OrderedDict
  import numpy
  from aix360.algorithms.dise import DISExplainer
  from aix360.algorithms.rule_induction.ripper.base import _encoding_for_parallel, init_encoder, encode_nominal, _split_instances
  from aix360.algorithms.rule_induction.ripper.binding import append_literal, _bind_literal, _bind_rule, unbound_rule_list_index, _unbound, _unbound_rule_list, _rule_list_predict, LE, EQ, _find_best_literal, Literal, _filter_contradicted_instances
  from aix360.algorithms.rule_induction.ripper.mdl import _mdl
  from aix360.algorithms.rule_induction.ripper.pruning import _pruning_irep, _minimize_rule_list, _pruning_optimization
  from aix360.algorithms.rule_induction.trxf.core.conjunction import Conjunction
  from aix360.algorithms.rule_induction.trxf.core.dnf_ruleset import DnfRuleSet
  from aix360.algorithms.rule_induction.trxf.core.feature import Feature
  from aix360.algorithms.rule_induction.trxf.core.predicate import Predicate, Relation
  from pandas import DataFrame, Series
label_desc: Use image node_id 7 for calling the RipperExplainer obj's underlying member method code with example usage: obj.explain_multiclass() and returns: res, DnfRuleSet