Packages

o

org.apache.spark.graphx.lib

SVDPlusPlus

object SVDPlusPlus

Implementation of SVD++ algorithm.

Source
SVDPlusPlus.scala
Linear Supertypes
AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. SVDPlusPlus
  2. AnyRef
  3. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Type Members

  1. class Conf extends Serializable

    Configuration parameters for SVDPlusPlus.

Value Members

  1. 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