org.apache.spark.ml.recommendation

Interface ALSParams

All Superinterfaces:

ALSModelParams, HasBlockSize, HasCheckpointInterval, HasMaxIter, HasPredictionCol, HasRegParam, HasSeed, Identifiable, Params, java.io.Serializable

All Known Implementing Classes:

ALS

public interface ALSParams
extends ALSModelParams, HasMaxIter, HasRegParam, HasCheckpointInterval, HasSeed

Common params for ALS.

Method Summary

Modifier and Type	Method and Description
DoubleParam	alpha() Param for the alpha parameter in the implicit preference formulation (nonnegative).
Param<String>	finalStorageLevel() Param for StorageLevel for ALS model factors.
double	getAlpha()
String	getFinalStorageLevel()
boolean	getImplicitPrefs()
String	getIntermediateStorageLevel()
boolean	getNonnegative()
int	getNumItemBlocks()
int	getNumUserBlocks()
int	getRank()
String	getRatingCol()
BooleanParam	implicitPrefs() Param to decide whether to use implicit preference.
Param<String>	intermediateStorageLevel() Param for StorageLevel for intermediate datasets.
BooleanParam	nonnegative() Param for whether to apply nonnegativity constraints.
IntParam	numItemBlocks() Param for number of item blocks (positive).
IntParam	numUserBlocks() Param for number of user blocks (positive).
IntParam	rank() Param for rank of the matrix factorization (positive).
Param<String>	ratingCol() Param for the column name for ratings.
StructType	validateAndTransformSchema(StructType schema) Validates and transforms the input schema.

Methods inherited from interface org.apache.spark.ml.recommendation.ALSModelParams

checkIntegers, coldStartStrategy, getColdStartStrategy, getItemCol, getUserCol, itemCol, userCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol

getPredictionCol, predictionCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasBlockSize

blockSize, getBlockSize

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.util.Identifiable

toString, uid

Methods inherited from interface org.apache.spark.ml.param.shared.HasMaxIter

getMaxIter, maxIter

Methods inherited from interface org.apache.spark.ml.param.shared.HasRegParam

getRegParam, regParam

Methods inherited from interface org.apache.spark.ml.param.shared.HasCheckpointInterval

checkpointInterval, getCheckpointInterval

Methods inherited from interface org.apache.spark.ml.param.shared.HasSeed

getSeed, seed

Method Detail

alpha

DoubleParam alpha()

Param for the alpha parameter in the implicit preference formulation (nonnegative). Default: 1.0

Returns:

(undocumented)

finalStorageLevel

Param<String> finalStorageLevel()

Param for StorageLevel for ALS model factors. Pass in a string representation of StorageLevel. Default: "MEMORY_AND_DISK".

Returns:

(undocumented)

getAlpha

double getAlpha()

getFinalStorageLevel

String getFinalStorageLevel()

getImplicitPrefs

boolean getImplicitPrefs()

getIntermediateStorageLevel

String getIntermediateStorageLevel()

getNonnegative

boolean getNonnegative()

getNumItemBlocks

int getNumItemBlocks()

getNumUserBlocks

int getNumUserBlocks()

getRank

int getRank()

getRatingCol

String getRatingCol()

implicitPrefs

BooleanParam implicitPrefs()

Param to decide whether to use implicit preference. Default: false

Returns:

(undocumented)

intermediateStorageLevel

Param<String> intermediateStorageLevel()

Param for StorageLevel for intermediate datasets. Pass in a string representation of StorageLevel. Cannot be "NONE". Default: "MEMORY_AND_DISK".

Returns:

(undocumented)

nonnegative

BooleanParam nonnegative()

Param for whether to apply nonnegativity constraints. Default: false

Returns:

(undocumented)

numItemBlocks

IntParam numItemBlocks()

Param for number of item blocks (positive). Default: 10

Returns:

(undocumented)

numUserBlocks

IntParam numUserBlocks()

Param for number of user blocks (positive). Default: 10

Returns:

(undocumented)

rank

IntParam rank()

Param for rank of the matrix factorization (positive). Default: 10

Returns:

(undocumented)

ratingCol

Param<String> ratingCol()

Param for the column name for ratings. Default: "rating"

Returns:

(undocumented)

validateAndTransformSchema

StructType validateAndTransformSchema(StructType schema)

Validates and transforms the input schema.

Parameters:

schema - input schema

Returns:

output schema