class AssociationRules extends Logging with Serializable
Generates association rules from a RDD[FreqItemset[Item]]
. This method only generates
association rules which have a single item as the consequent.
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- @Since( "1.5.0" )
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- AssociationRules.scala
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new
AssociationRules()
Constructs a default instance with default parameters {minConfidence = 0.8}.
Constructs a default instance with default parameters {minConfidence = 0.8}.
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logInfo(msg: ⇒ String): Unit
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logName: String
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def
run[Item](freqItemsets: JavaRDD[FreqItemset[Item]]): JavaRDD[Rule[Item]]
Java-friendly version of
run
.Java-friendly version of
run
.- Annotations
- @Since( "1.5.0" )
-
def
run[Item](freqItemsets: RDD[FreqItemset[Item]], itemSupport: Map[Item, Double])(implicit arg0: ClassTag[Item]): RDD[Rule[Item]]
Computes the association rules with confidence above
minConfidence
.Computes the association rules with confidence above
minConfidence
.- freqItemsets
frequent itemset model obtained from FPGrowth
- itemSupport
map containing an item and its support
- returns
a
RDD[Rule[Item]]
containing the association rules. The rules will be able to compute also the lift metric.
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- @Since( "2.4.0" )
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def
run[Item](freqItemsets: RDD[FreqItemset[Item]])(implicit arg0: ClassTag[Item]): RDD[Rule[Item]]
Computes the association rules with confidence above
minConfidence
.Computes the association rules with confidence above
minConfidence
.- freqItemsets
frequent itemset model obtained from FPGrowth
- returns
a
RDD[Rule[Item]]
containing the association rules.
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- @Since( "1.5.0" )
-
def
setMinConfidence(minConfidence: Double): AssociationRules.this.type
Sets the minimal confidence (default:
0.8
).Sets the minimal confidence (default:
0.8
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