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org.apache.spark.graphx.lib

SVDPlusPlus

object SVDPlusPlus

Implementation of SVD++ algorithm.

Source
SVDPlusPlus.scala
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  1. class Conf extends Serializable

    Configuration parameters for SVDPlusPlus.

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  15. def run(edges: RDD[Edge[Double]], conf: Conf): (Graph[(Array[Double], Array[Double], Double, Double), Double], Double)

    Implement SVD++ based on "Factorization Meets the Neighborhood: a Multifaceted Collaborative Filtering Model", available at here.

    Implement SVD++ based on "Factorization Meets the Neighborhood: a Multifaceted Collaborative Filtering Model", available at here.

    The prediction rule is rui = u + bu + bi + qi*(pu + |N(u)|-0.5*sum(y)), see the details on page 6.

    edges

    edges for constructing the graph

    conf

    SVDPlusPlus parameters

    returns

    a graph with vertex attributes containing the trained model

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