我有以下数据集：
[A,D]
[C,A,B]
[A]
[A,E,D]
[B,D]
我正在尝试使用 Spark Mllib 使用频繁模式挖掘来提取一些关联规则。为此，我有以下代码：
val transactions = sc.textFile("/user/cloudera/teste")
import org.apache.spark.mllib.fpm.AssociationRules
import org.apache.spark.mllib.fpm.FPGrowth.FreqItemset
val freqItemsets = transactions.repartition(10).map(_.split(",")).flatMap(xs =>
(xs.combinations(1) ++ xs.combinations(2) ++ xs.combinations(3) ++ xs.combinations(4) ++ xs.combinations(5)).filter(_.nonEmpty).map(x => (x.toList, 1L)) ).reduceByKey(_ + _).map{case (xs, cnt) => new FreqItemset(xs.toArray, cnt)}
val ar = new AssociationRules().setMinConfidence(0.8)
val results = ar.run(freqItemsets)
results.collect().foreach { rule =>
println("[" + rule.antecedent.mkString(",")
+ "=>"
+ rule.consequent.mkString(",") + "]," + rule.confidence)}
但是提取的所有规则的置信度都等于 1：
[[C=>A],1.0
[[C=>B]],1.0
[A,B]=>[C],1.0
[E=>D]],1.0
[E=>[A],1.0
[A=>B]],1.0
[A=>[C],1.0
[[C,A=>B]],1.0
[[A=>D]],1.0
[E,D]=>[A],1.0
[[A,E=>D]],1.0
[[C,B]=>A],1.0
[[B=>D]],1.0
[B]=>A],1.0
[B]=>[C],1.0
我真的不明白我在代码中遇到的问题......任何人都知道我必须计算置信度的错误是什么？
非常感谢！