Från regler till grafbaserade visualiseringar

Kundkorgsanalys i R

Christopher Bruffaerts

Statistician

Visualisera regler

Interaktiva regler

rules_html = plot(rules, method = "graph",
                  engine = "htmlwidget")
rules_html

Spara HTML-widgeten

library(htmlwidgets)
saveWidget(rules_html, file = "rules_grocery.html")

graph_rules

Välj objekt och regler från grafen

Välj objektet Bread

graph_rule_bread

Välj regel 3

graph_rule3

Grafer och delgrafer (1)

Sortera regler efter konfidens

top4subRules = 
    head(sort(rules, by = "confidence"), 4)
inspect(top4subRules)

    lhs         rhs      support   confidence lift      count
[1] {Bread}  => {Butter} 0.4285714 1.00       1.1666667 3    
[2] {Wine}   => {Butter} 0.5714286 0.80       0.9333333 4    
[3] {Cheese} => {Wine}   0.4285714 0.75       1.0500000 3    
[4] {Cheese} => {Butter} 0.4285714 0.75       0.8750000 3

Plotta regler med hög konfidens

plot(top4subRules, method = "graph",  engine = "htmlwidget")

graph_rules_confidence

Grafer och delgrafer (2)

Inspektera ostregler

C_rules = 
    apriori(data = data_trx, 
            parameter = list(supp = 3/7,
                             conf = 0.2,
                             minlen = 2),
            appearance = list(rhs = "Cheese"))
inspect(C_rules)

    lhs         rhs      support   confidence lift  count
[1] {Wine}   => {Cheese} 0.4285714 0.6        1.050 3    
[2] {Butter} => {Cheese} 0.4285714 0.5        0.875 3

Plotta ostregler

plot(C_rules, method = "graph",  engine = "htmlwidget")

graph_rules_cheese

Spara som graf

Spara din graf

saveAsGraph(rules, file = "rules.graphml")

Nu kör vi en övning!

Kundkorgsanalys i R