Measure | Formula | |
---|---|---|
Support The support defined as the proportion of transaction in the database, which contains the items A [2] | \(Support(A \to B) = \frac{|t(A \cup B)|}{t(A)}\) | (1) |
Confidence The confidence determines how frequently items in B appear in transaction that contains A [2], ranges from 0 to 1 | \(Confidence(A \to B) = \frac{Support(A \cup B)}{Support(A)}\) | (2) |
Lift The lift measures how far from independence are A and B [16]. It ranges within [0, +∞] | \(Lift(A \to B) = \frac{Support(A \cup B)}{Support(A)*Support(B)}\) | (9) |
Laplace It is a confidence estimator that takes support into account [17]. It ranges within [0, 1] | \(lapl(A \to B) = \frac{Support(A \cup B) + 1}{Support(A) + 2}\) | (10) |
Conviction Measure the degree of implication of a rule [18]. It ranges along the values [0.25, +∞] | \(conv(A \to B) = \frac{1 - Support(B)}{1 - conf(A \to B)}\) | (11) |
Leverage Measure how much more counting is obtained from the co-occurrence of the antecedent and consequent from the independence [19] | \(leve\left( {A \to B} \right) = Support\left( {A \to B} \right) - Support\left( A \right) \, \times \, Support\left( B \right)\) | (12) |
Jaccard Measure the degree of overlap between the cases covered by each of them [20] the Jaccard coefficient takes values in [0, 1] | \(Jacc(A \to B) = \frac{Support(A \cup B)}{Support(A)\, + \,Support(B) - Support(A \cup B)}\) | (13) |
Ï•-Coefficient This measure can be used to measure the association between A and B [21] | \(\phi (A \to B) = \frac{leve(A \cup B)}{{\sqrt {(Support(A)\, \times \,Support(B))\, \times \,(1 - Support(A))\, \times \,(1 - Support(B)} )}}\) | (14) |