Question

我试图将ARules算法的输出转换为适当的数据集。这是我得到的示例输出

以下是生成它的示例代码。

data("Adult")
## Mine association rules.
rules <- apriori(Adult, 
                 parameter = list(supp = 0.5, conf = 0.9,
                                  target = "rules"))

ruledf = data.frame(
  lhs = labels(lhs(rules)),
  rhs = labels(rhs(rules)), 
  rules@quality)

head(ruled)

                         lhs                 rhs   support confidence      lift count
1                         {} {capital-gain=None} 0.9173867  0.9173867 1.0000000 44807
2                         {} {capital-loss=None} 0.9532779  0.9532779 1.0000000 46560
3 {hours-per-week=Full-time} {capital-gain=None} 0.5435895  0.9290688 1.0127342 26550
4 {hours-per-week=Full-time} {capital-loss=None} 0.5606650  0.9582531 1.0052191 27384
5                 {sex=Male} {capital-gain=None} 0.6050735  0.9051455 0.9866565 29553
6                 {sex=Male} {capital-loss=None} 0.6331027  0.9470750 0.9934931 30922

我将只考虑lhs rhs列用于我的数据操作

以下是我希望如何将上述内容转换为以下结构的示例。

sex  hours-per-week capital-gain
NA   Full-time      None
NA   Full-time      None
Male        NA      None
Male        NA      None

提前致谢

数据与R争用字符串数据

0 个答案: