ex_fuzzy.rule_mining.multiclass_mine_rulebase#
- ex_fuzzy.rule_mining.multiclass_mine_rulebase(x, y, fuzzy_variables, support_threshold=0.05, max_depth=3, confidence_threshold=0.05, lift_threshold=1.05)[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.
- Parameters:
x (DataFrame) – the data to mine. Dims: samples x features.
fuzzy_variables (list[fuzzyVariable]) – list of the fuzzy variables for each of the input variables.
support_threshold (float) – minimum threshold to decide if prune or not the rule.
max_depth (int) – maximum number of antecedents per rule.
confidence_threshold (float) – minimum confidence value.
lift_threshold (float)
- Returns:
a rulebase object with the rules denoted as good.
- Return type: