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From feynmanliang <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-8559][MLlib] Support Association Rule G...
Date Tue, 07 Jul 2015 17:44:40 GMT
Github user feynmanliang commented on a diff in the pull request:

    https://github.com/apache/spark/pull/7005#discussion_r34068106
  
    --- Diff: mllib/src/main/scala/org/apache/spark/mllib/fpm/AssociationRules.scala ---
    @@ -0,0 +1,119 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +package org.apache.spark.mllib.fpm
    +
    +import scala.reflect.ClassTag
    +
    +import org.apache.spark.Logging
    +import org.apache.spark.annotation.Experimental
    +import org.apache.spark.api.java.JavaRDD
    +import org.apache.spark.api.java.JavaSparkContext.fakeClassTag
    +import org.apache.spark.mllib.fpm.AssociationRules.Rule
    +import org.apache.spark.mllib.fpm.FPGrowth.FreqItemset
    +import org.apache.spark.rdd.RDD
    +
    +/**
    + * :: Experimental ::
    + *
    + * Generates association rules from a [[RDD[FreqItemset[Item]]]. This method only generates
    + * association rules which have a single item as the consequent.
    + */
    +@Experimental
    +class AssociationRules private (
    +    private var minConfidence: Double) extends Logging with Serializable {
    +
    +  /**
    +   * Constructs a default instance with default parameters {minConfidence = 0.8}.
    +   */
    +  def this() = this(0.8)
    +
    +  /**
    +   * Sets the minimal confidence (default: `0.8`).
    +   */
    +  def setMinConfidence(minConfidence: Double): this.type = {
    +    this.minConfidence = minConfidence
    +    this
    +  }
    +
    +  /**
    +   * Computes the association rules with confidence above [[minConfidence]].
    +   * @param freqItemsets frequent itemset model obtained from [[FPGrowth]]
    +   * @return a [[Set[Rule[Item]]] containing the assocation rules.
    +   */
    +  def run[Item: ClassTag](freqItemsets: RDD[FreqItemset[Item]]): RDD[Rule[Item]] = {
    +    freqItemsets.flatMap { itemset =>
    +      val items = itemset.items
    +      items.flatMap { item =>
    +        items.partition(_ == item) match {
    +          // Itemsets and items in itemsets are unique, so every (antecedent, consequent)
is unique
    +          case (consequent, antecedent) if !antecedent.isEmpty =>
    +            Some((antecedent.toSeq, (consequent.toSeq, itemset.freq)))
    +          case _ => None
    +        }
    +      } :+ (items.toSeq, (Nil, itemset.freq))
    +    }.aggregateByKey(Map[Seq[Item], Long]().empty)(
    --- End diff --
    
    OK.


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