org.apache.spark.mllib.recommendation

MatrixFactorizationModel

class MatrixFactorizationModel extends Serializable

Model representing the result of matrix factorization.

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  17. def predict(usersProductsJRDD: JavaRDD[Array[Byte]]): JavaRDD[Array[Byte]]

    :: DeveloperApi :: Predict the rating of many users for many products.

    :: DeveloperApi :: Predict the rating of many users for many products. This is a Java stub for python predictAll()

    usersProductsJRDD

    A JavaRDD with serialized tuples (user, product)

    returns

    JavaRDD of serialized Rating objects.

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    @DeveloperApi()
  18. def predict(usersProducts: RDD[(Int, Int)]): RDD[Rating]

    Predict the rating of many users for many products.

    Predict the rating of many users for many products. The output RDD has an element per each element in the input RDD (including all duplicates) unless a user or product is missing in the training set.

    usersProducts

    RDD of (user, product) pairs.

    returns

    RDD of Ratings.

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

    Predict the rating of one user for one product.

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

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

  21. val rank: Int

    Rank for the features in this model.

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

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

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

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