# is.significant

##### Find Significant Rules

Provides the generic functions and the S4 method `is.significant`

to find rules where the LHS and the RHS depend on each other. This uses
Fisher's exact test and corrects for multiple comparisons.

- Keywords
- manip

##### Usage

```
is.significant(x, transactions, method = "fisher",
alpha = 0.01, adjust = "bonferroni")
```

##### Arguments

- x
a set of rules.

- transactions
set of transactions used to mine the rules.

- method
test to use. Options are

`"fisher", "chisq"`

. Note that the contingency table is likely to have cells with low expected values and that thus Fisher's Exact Test might be more appropriate than the chi-squared test.- alpha
required significance level.

- adjust
method to adjust for multiple comparisons. Options are

`"none", "bonferroni", "holm", "fdr"`

, etc. (see`p.adjust`

)

##### Value

returns a logical vector indicating which rules are significant.

##### See Also

##### Examples

```
# NOT RUN {
data("Income")
rules <- apriori(Income, parameter = list(support = 0.5))
is.significant(rules, Income)
inspect(rules[is.significant(rules, Income)])
# }
```

*Documentation reproduced from package arules, version 1.5-5, License: GPL-3*