Metrics visualiseren

Market Basket-analyse in R

Christopher Bruffaerts

Statistician

Interactieve tabel met metrics

Regels uit de supermarkt

library(arules)
rules = apriori(data_trx, 
                parameter = list(
                  supp = 3/7, conf=0.6, minlen=2)
                )
inspect(rules)

Interactieve tabel

library(arulesViz)
inspectDT(rules)

HTML-tabel

inspect_DT_rule

Introductie scatterplots

Regels inspecteren

inspect(rules)

    lhs         rhs      support   confidence lift      count
[1] {Bread}  => {Butter} 0.4285714 1.0000000  1.1666667 3    
[2] {Cheese} => {Wine}   0.4285714 0.7500000  1.0500000 3    
[3] {Wine}   => {Cheese} 0.4285714 0.6000000  1.0500000 3    
[4] {Cheese} => {Butter} 0.4285714 0.7500000  0.8750000 3    
[5] {Wine}   => {Butter} 0.5714286 0.8000000  0.9333333 4    
[6] {Butter} => {Wine}   0.5714286 0.6666667  0.9333333 4

Scatterplot uit arulesViz

plot(rules)

scatter_grocery

Flexibele arules-plots

Plotopties

plot(rulesObject, measure, shading, method)

rulesObject: het rules-object om te plotten
measure: Maten voor regelinteressantheid (support, confidence, lift, ...)
shading: Maat voor puntkleuring
method: Te gebruiken visualisatie ("scatterplot", "matrix", "two-key plot", "matrix3D")

Voorbeeld

plot(rules, measure = c("confidence", "lift"),
     shading = "support",
     method = "scatterplot")

scatter_grocery_plot

Andere arules-plots

Two-key-plot

plot(rules, method = "two-key plot")

two_key_plot

Jitter toepassen op je plots

Zonder jitter

plot(rules, method = "two-key plot")

two_key_plot

Met jitter

plot(rules, method = "two-key plot",jitter = 2)

two_key_plot_jitter

Interactieve arules-plots

Interactieve regels

plot(rules, engine = "plotly")

Van statisch naar interactief

rules_plotly

Laten we metrics visualiseren!

Market Basket-analyse in R