org.apache.spark.mllib.recommendation

Class ALS

Object

org.apache.spark.mllib.recommendation.ALS

All Implemented Interfaces:

java.io.Serializable, Logging

public class ALS
extends Object
implements scala.Serializable, Logging

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
ALS()

Method Summary

Methods

Modifier and Type	Method and Description
MatrixFactorizationModel	run(JavaRDD<Rating> ratings)
MatrixFactorizationModel	run(RDD<Rating> ratings)
ALS	setAlpha(double alpha)
ALS	setBlocks(int numBlocks)
ALS	setCheckpointInterval(int checkpointInterval)
ALS	setFinalRDDStorageLevel(StorageLevel storageLevel)
ALS	setImplicitPrefs(boolean implicitPrefs)
ALS	setIntermediateRDDStorageLevel(StorageLevel storageLevel)
ALS	setIterations(int iterations)
ALS	setLambda(double lambda)
ALS	setNonnegative(boolean b)
ALS	setProductBlocks(int numProductBlocks)
ALS	setRank(int rank)
ALS	setSeed(long seed)
ALS	setUserBlocks(int numUserBlocks)
static MatrixFactorizationModel	train(RDD<Rating> ratings, int rank, int iterations)
static MatrixFactorizationModel	train(RDD<Rating> ratings, int rank, int iterations, double lambda)
static MatrixFactorizationModel	train(RDD<Rating> ratings, int rank, int iterations, double lambda, int blocks)
static MatrixFactorizationModel	train(RDD<Rating> ratings, int rank, int iterations, double lambda, int blocks, long seed)
static MatrixFactorizationModel	trainImplicit(RDD<Rating> ratings, int rank, int iterations)
static MatrixFactorizationModel	trainImplicit(RDD<Rating> ratings, int rank, int iterations, double lambda, double alpha)
static MatrixFactorizationModel	trainImplicit(RDD<Rating> ratings, int rank, int iterations, double lambda, int blocks, double alpha)
static MatrixFactorizationModel	trainImplicit(RDD<Rating> ratings, int rank, int iterations, double lambda, int blocks, double alpha, long seed)

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.Logging

initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Constructor Detail

ALS

public ALS()

Method Detail

train

public static MatrixFactorizationModel train(RDD<Rating> ratings,
                             int rank,
                             int iterations,
                             double lambda,
                             int blocks,
                             long seed)

train

public static MatrixFactorizationModel train(RDD<Rating> ratings,
                             int rank,
                             int iterations,
                             double lambda,
                             int blocks)

train

public static MatrixFactorizationModel train(RDD<Rating> ratings,
                             int rank,
                             int iterations,
                             double lambda)

train

public static MatrixFactorizationModel train(RDD<Rating> ratings,
                             int rank,
                             int iterations)

trainImplicit

public static MatrixFactorizationModel trainImplicit(RDD<Rating> ratings,
                                     int rank,
                                     int iterations,
                                     double lambda,
                                     int blocks,
                                     double alpha,
                                     long seed)

trainImplicit

public static MatrixFactorizationModel trainImplicit(RDD<Rating> ratings,
                                     int rank,
                                     int iterations,
                                     double lambda,
                                     int blocks,
                                     double alpha)

trainImplicit

public static MatrixFactorizationModel trainImplicit(RDD<Rating> ratings,
                                     int rank,
                                     int iterations,
                                     double lambda,
                                     double alpha)

trainImplicit

public static MatrixFactorizationModel trainImplicit(RDD<Rating> ratings,
                                     int rank,
                                     int iterations)

setBlocks

public ALS setBlocks(int numBlocks)

setUserBlocks

public ALS setUserBlocks(int numUserBlocks)

setProductBlocks

public ALS setProductBlocks(int numProductBlocks)

setRank

public ALS setRank(int rank)

setIterations

public ALS setIterations(int iterations)

setLambda

public ALS setLambda(double lambda)

setImplicitPrefs

public ALS setImplicitPrefs(boolean implicitPrefs)

setAlpha

public ALS setAlpha(double alpha)

setSeed

public ALS setSeed(long seed)

setNonnegative

public ALS setNonnegative(boolean b)

setIntermediateRDDStorageLevel

public ALS setIntermediateRDDStorageLevel(StorageLevel storageLevel)

setFinalRDDStorageLevel

public ALS setFinalRDDStorageLevel(StorageLevel storageLevel)

setCheckpointInterval

public ALS setCheckpointInterval(int checkpointInterval)

run

public MatrixFactorizationModel run(RDD<Rating> ratings)

run

public MatrixFactorizationModel run(JavaRDD<Rating> ratings)