ex_fuzzy.rule_mining.simple_multiclass_mine_rulebase#

ex_fuzzy.rule_mining.simple_multiclass_mine_rulebase(x, y, fuzzy_type, support_threshold=0.05, max_depth=3, confidence_threshold=0.5, lift_threshold=1.1)[source]#

Search the data for associations that are frequent and have good confidence/lift values given a list of fuzzy variables for each antecedent. Computes a different ruleBase for each class and then uses them to form a MasterRuleBase.

Computes the fuzzy variables using a 3 label partition (low, medium, high).

Parameters:

  • x (DataFrame) – the data to mine. Dims: samples x features.

  • fuzzy_type (FUZZY_SETS) – fuzzy type to use.

  • support_threshold (float) – minimum threshold to decide if prune or not the rule.

  • max_depth (int) – maximum number of antecedents per rule.

Returns:

a rulebase object with the rules denoted as good.

Return type:

MasterRuleBase