class_docstr: This class implements a simple classifier constructed from a list of DNF rule sets.
  Based on the specified RuleSelectionMethod, this classifier predicts the label for a given input.
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docstr: @param rule_sets: A list of dnf rule sets
  @param rule_selection_method: Conflict resolution strategy for multiple fired rules
  @param confidence_metric: Rule confidence definition to use
  @param weight_metric: Rule weight definition to use depending on RuleSelectionMethod
  @param default_label: Optional default label to be returned when no rule set matches the data input.
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code: def __init__(
      self,
      rule_sets: List[DnfRuleSet],
      rule_selection_method: RuleSelectionMethod,
      confidence_metric: ConfidenceMetric = None,
      weight_metric: WeightMetric = None,
      default_label: Any = None,
  ):
      """
      @param rule_sets: A list of dnf rule sets
      @param rule_selection_method: Conflict resolution strategy for multiple fired rules
      @param confidence_metric: Rule confidence definition to use
      @param weight_metric: Rule weight definition to use depending on RuleSelectionMethod
      @param default_label: Optional default label to be returned when no rule set matches the data input.
      """
      self._rule_sets = rule_sets
      self._rule_selection_method = rule_selection_method
      self._default_label = default_label
      self._confidence_metric = confidence_metric
      self._weight_metric = weight_metric
      self._rules = [
          Rule(
              conjunction=c,
              label=ruleset.then_part,
              record_count=None,
              nb_correct=None,
              confidence=None,
              weight=None,
          )
          for ruleset in self._rule_sets
          for c in ruleset.conjunctions
      ]
  
imports: import enum
  from collections import namedtuple
  from typing import Dict, List, Any
  import pandas
  from aix360.algorithms.rule_induction.trxf.core.dnf_ruleset import DnfRuleSet
  from aix360.algorithms.rule_induction.trxf.metrics import compute_rule_metrics
label_desc: Use image node_id 1 to create a new RuleSetClassifier object  with example: obj = RuleSetClassifier(rule_sets, rule_selection_method, confidence_metric, weight_metric, default_label)