Contents
What is the confidence for the rules?
The confidence of an association rule is a percentage value that shows how frequently the rule head occurs among all the groups containing the rule body. Thus, the confidence of a rule is the percentage equivalent of m/n, where the values are: m. The number of groups containing the joined rule head and rule body.
What is support and confidence in association rule mining?
Association rule mining, at a basic level, involves the use of machine learning models to analyze data for patterns, or co-occurrences, in a database. Support is an indication of how frequently the items appear in the data. Confidence indicates the number of times the if-then statements are found true.
How do you calculate confidence in association rule?
The confidence of an association rule is the support of (X U Y) divided by the support of X. Therefore, the confidence of the association rule is in this case the support of (2,5,3) divided by the support of (2,5). i.e. a number of transactions in which both A and B are present.
How to calculate the confidence for an association rule?
The confidence for an association rule having a very frequent consequent will always be high. I will introduce some numbers here to clarify this further. Total transactions = 100. 10 of them have both milk and toothbrush, 70 have milk but no toothbrush and 4 have toothbrush but no milk. Consider the numbers from figure on the left.
Which is an example of a high confidence rule?
We can say by common knowledge that {Captain Crunch} → {Milk} should be a high confidence rule. Technically, confidence is the conditional probability of occurrence of consequent given the antecedent. Let us consider few more examples before moving ahead.
How to prove the probability of a null set is 0?
A text states that you can prove that a probability of a null set is 0 through one of the axioms of probability. I know the three axioms, but I fail to employ these axioms to prove the above.
Which is an association rule with a very frequent consequent?
Confidence for this rule will also be high since {Milk} is such a frequent itemset and would be present in every other transaction. It does not matter what you have in the antecedent for such a frequent consequent. The confidence for an association rule having a very frequent consequent will always be high.