Machine Learning with R Cookbook - Second Edition

How to do it...

Perform the following steps to prune redundant rules:

1. First, follow these steps to find redundant rules:

        > rules.sorted = sort(rules, by="lift")
        > subset.matrix = is.subset(rules.sorted, rules.sorted)
        > subset.matrix[lower.tri(subset.matrix, diag=T)] = NA
        > redundant = colSums(subset.matrix, na.rm=T) >= 1  

2. You can then remove redundant rules:

        > rules.pruned = rules.sorted[!redundant]
        > inspect(head(rules.pruned))
        Output
        lhsrhs                  support confidence     lift
        1 {Instant food products,                                                    
        soda}                  => {hamburger meat} 0.001220132  0.6315789        18.99565
        2 {soda,                                                                     
        popcorn}               => {salty snack}    0.001220132  0.6315789        16.69779
        3 {flour,                                                                    
        baking powder}         => {sugar}          0.001016777  0.5555556 16.40807 4 {ham, processed cheese} => {white bread} 0.001931876 ...