org.apache.spark.mllib.recommendation

MatrixFactorizationModel

class MatrixFactorizationModel extends Serializable

Model representing the result of matrix factorization.

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  1. MatrixFactorizationModel
  2. Serializable
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Instance Constructors

  1. new MatrixFactorizationModel(rank: Int, userFeatures: RDD[(Int, Array[Double])], productFeatures: RDD[(Int, Array[Double])])

    rank

    Rank for the features in this model.

    userFeatures

    RDD of tuples where each tuple represents the userId and the features computed for this user.

    productFeatures

    RDD of tuples where each tuple represents the productId and the features computed for this product.

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  1. final def !=(arg0: AnyRef): Boolean

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  7. def clone(): AnyRef

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  10. def finalize(): Unit

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  11. final def getClass(): java.lang.Class[_]

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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  17. def predict(user: Int, product: Int): Double

    Predict the rating of one user for one product.

  18. val productFeatures: RDD[(Int, Array[Double])]

    RDD of tuples where each tuple represents the productId and the features computed for this product.

  19. val rank: Int

    Rank for the features in this model.

  20. final def synchronized[T0](arg0: ⇒ T0): T0

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  21. def toString(): String

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  22. val userFeatures: RDD[(Int, Array[Double])]

    RDD of tuples where each tuple represents the userId and the features computed for this user.

  23. final def wait(): Unit

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  24. final def wait(arg0: Long, arg1: Int): Unit

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  25. final def wait(arg0: Long): Unit

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