class ALSModel extends Model[ALSModel] with ALSModelParams with MLWritable
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final
def
!=(arg0: Any): Boolean
- Definition Classes
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final
def
##(): Int
- Definition Classes
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final
def
$[T](param: Param[T]): T
An alias for
getOrDefault()
.An alias for
getOrDefault()
.- Attributes
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final
def
==(arg0: Any): Boolean
- Definition Classes
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final
def
asInstanceOf[T0]: T0
- Definition Classes
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final
val
blockSize: IntParam
Param for block size for stacking input data in matrices.
Param for block size for stacking input data in matrices. Data is stacked within partitions. If block size is more than remaining data in a partition then it is adjusted to the size of this data..
- Definition Classes
- HasBlockSize
-
def
checkIntegers(dataset: Dataset[_], colName: String): Column
Attempts to safely cast a user/item id to an Int.
Attempts to safely cast a user/item id to an Int. Throws an exception if the value is out of integer range or contains a fractional part.
- Attributes
- protected[recommendation]
- Definition Classes
- ALSModelParams
-
final
def
clear(param: Param[_]): ALSModel.this.type
Clears the user-supplied value for the input param.
Clears the user-supplied value for the input param.
- Definition Classes
- Params
-
def
clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
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- @throws( ... ) @native() @IntrinsicCandidate()
-
val
coldStartStrategy: Param[String]
Param for strategy for dealing with unknown or new users/items at prediction time.
Param for strategy for dealing with unknown or new users/items at prediction time. This may be useful in cross-validation or production scenarios, for handling user/item ids the model has not seen in the training data. Supported values: - "nan": predicted value for unknown ids will be NaN. - "drop": rows in the input DataFrame containing unknown ids will be dropped from the output DataFrame containing predictions. Default: "nan".
- Definition Classes
- ALSModelParams
-
def
copy(extra: ParamMap): ALSModel
Creates a copy of this instance with the same UID and some extra params.
Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See
defaultCopy()
.- Definition Classes
- ALSModel → Model → Transformer → PipelineStage → Params
- Annotations
- @Since( "1.5.0" )
-
def
copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T
Copies param values from this instance to another instance for params shared by them.
Copies param values from this instance to another instance for params shared by them.
This handles default Params and explicitly set Params separately. Default Params are copied from and to
defaultParamMap
, and explicitly set Params are copied from and toparamMap
. Warning: This implicitly assumes that this Params instance and the target instance share the same set of default Params.- to
the target instance, which should work with the same set of default Params as this source instance
- extra
extra params to be copied to the target's
paramMap
- returns
the target instance with param values copied
- Attributes
- protected
- Definition Classes
- Params
-
final
def
defaultCopy[T <: Params](extra: ParamMap): T
Default implementation of copy with extra params.
Default implementation of copy with extra params. It tries to create a new instance with the same UID. Then it copies the embedded and extra parameters over and returns the new instance.
- Attributes
- protected
- Definition Classes
- Params
-
final
def
eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
def
equals(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
def
explainParam(param: Param[_]): String
Explains a param.
Explains a param.
- param
input param, must belong to this instance.
- returns
a string that contains the input param name, doc, and optionally its default value and the user-supplied value
- Definition Classes
- Params
-
def
explainParams(): String
Explains all params of this instance.
Explains all params of this instance. See
explainParam()
.- Definition Classes
- Params
-
final
def
extractParamMap(): ParamMap
extractParamMap
with no extra values.extractParamMap
with no extra values.- Definition Classes
- Params
-
final
def
extractParamMap(extra: ParamMap): ParamMap
Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.
Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.
- Definition Classes
- Params
-
final
def
get[T](param: Param[T]): Option[T]
Optionally returns the user-supplied value of a param.
Optionally returns the user-supplied value of a param.
- Definition Classes
- Params
-
final
def
getBlockSize: Int
- Definition Classes
- HasBlockSize
-
final
def
getClass(): Class[_]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @IntrinsicCandidate()
-
def
getColdStartStrategy: String
- Definition Classes
- ALSModelParams
-
final
def
getDefault[T](param: Param[T]): Option[T]
Gets the default value of a parameter.
Gets the default value of a parameter.
- Definition Classes
- Params
-
def
getItemCol: String
- Definition Classes
- ALSModelParams
-
final
def
getOrDefault[T](param: Param[T]): T
Gets the value of a param in the embedded param map or its default value.
Gets the value of a param in the embedded param map or its default value. Throws an exception if neither is set.
- Definition Classes
- Params
-
def
getParam(paramName: String): Param[Any]
Gets a param by its name.
Gets a param by its name.
- Definition Classes
- Params
-
final
def
getPredictionCol: String
- Definition Classes
- HasPredictionCol
-
def
getUserCol: String
- Definition Classes
- ALSModelParams
-
final
def
hasDefault[T](param: Param[T]): Boolean
Tests whether the input param has a default value set.
Tests whether the input param has a default value set.
- Definition Classes
- Params
-
def
hasParam(paramName: String): Boolean
Tests whether this instance contains a param with a given name.
Tests whether this instance contains a param with a given name.
- Definition Classes
- Params
-
def
hasParent: Boolean
Indicates whether this Model has a corresponding parent.
-
def
hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @IntrinsicCandidate()
-
def
initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
- Attributes
- protected
- Definition Classes
- Logging
-
def
initializeLogIfNecessary(isInterpreter: Boolean): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
final
def
isDefined(param: Param[_]): Boolean
Checks whether a param is explicitly set or has a default value.
Checks whether a param is explicitly set or has a default value.
- Definition Classes
- Params
-
final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
-
final
def
isSet(param: Param[_]): Boolean
Checks whether a param is explicitly set.
Checks whether a param is explicitly set.
- Definition Classes
- Params
-
def
isTraceEnabled(): Boolean
- Attributes
- protected
- Definition Classes
- Logging
-
val
itemCol: Param[String]
Param for the column name for item ids.
Param for the column name for item ids. Ids must be integers. Other numeric types are supported for this column, but will be cast to integers as long as they fall within the integer value range. Default: "item"
- Definition Classes
- ALSModelParams
- val itemFactors: DataFrame
-
def
log: Logger
- Attributes
- protected
- Definition Classes
- Logging
-
def
logDebug(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
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def
logDebug(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
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def
logError(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logError(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logInfo(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logInfo(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logName: String
- Attributes
- protected
- Definition Classes
- Logging
-
def
logTrace(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logTrace(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logWarning(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logWarning(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
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final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
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final
def
notify(): Unit
- Definition Classes
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- Annotations
- @native() @IntrinsicCandidate()
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final
def
notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @IntrinsicCandidate()
-
lazy val
params: Array[Param[_]]
Returns all params sorted by their names.
Returns all params sorted by their names. The default implementation uses Java reflection to list all public methods that have no arguments and return Param.
- Definition Classes
- Params
- Note
Developer should not use this method in constructor because we cannot guarantee that this variable gets initialized before other params.
-
var
parent: Estimator[ALSModel]
The parent estimator that produced this model.
The parent estimator that produced this model.
- Definition Classes
- Model
- Note
For ensembles' component Models, this value can be null.
-
final
val
predictionCol: Param[String]
Param for prediction column name.
Param for prediction column name.
- Definition Classes
- HasPredictionCol
-
val
rank: Int
- Annotations
- @Since( "1.4.0" )
-
def
recommendForAllItems(numUsers: Int): DataFrame
Returns top
numUsers
users recommended for each item, for all items.Returns top
numUsers
users recommended for each item, for all items.- numUsers
max number of recommendations for each item
- returns
a DataFrame of (itemCol: Int, recommendations), where recommendations are stored as an array of (userCol: Int, rating: Float) Rows.
- Annotations
- @Since( "2.2.0" )
-
def
recommendForAllUsers(numItems: Int): DataFrame
Returns top
numItems
items recommended for each user, for all users.Returns top
numItems
items recommended for each user, for all users.- numItems
max number of recommendations for each user
- returns
a DataFrame of (userCol: Int, recommendations), where recommendations are stored as an array of (itemCol: Int, rating: Float) Rows.
- Annotations
- @Since( "2.2.0" )
-
def
recommendForItemSubset(dataset: Dataset[_], numUsers: Int): DataFrame
Returns top
numUsers
users recommended for each item id in the input data set.Returns top
numUsers
users recommended for each item id in the input data set. Note that if there are duplicate ids in the input dataset, only one set of recommendations per unique id will be returned.- dataset
a Dataset containing a column of item ids. The column name must match
itemCol
.- numUsers
max number of recommendations for each item.
- returns
a DataFrame of (itemCol: Int, recommendations), where recommendations are stored as an array of (userCol: Int, rating: Float) Rows.
- Annotations
- @Since( "2.3.0" )
-
def
recommendForUserSubset(dataset: Dataset[_], numItems: Int): DataFrame
Returns top
numItems
items recommended for each user id in the input data set.Returns top
numItems
items recommended for each user id in the input data set. Note that if there are duplicate ids in the input dataset, only one set of recommendations per unique id will be returned.- dataset
a Dataset containing a column of user ids. The column name must match
userCol
.- numItems
max number of recommendations for each user.
- returns
a DataFrame of (userCol: Int, recommendations), where recommendations are stored as an array of (itemCol: Int, rating: Float) Rows.
- Annotations
- @Since( "2.3.0" )
-
def
save(path: String): Unit
Saves this ML instance to the input path, a shortcut of
write.save(path)
.Saves this ML instance to the input path, a shortcut of
write.save(path)
.- Definition Classes
- MLWritable
- Annotations
- @Since( "1.6.0" ) @throws( ... )
-
final
def
set(paramPair: ParamPair[_]): ALSModel.this.type
Sets a parameter in the embedded param map.
Sets a parameter in the embedded param map.
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set(param: String, value: Any): ALSModel.this.type
Sets a parameter (by name) in the embedded param map.
Sets a parameter (by name) in the embedded param map.
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set[T](param: Param[T], value: T): ALSModel.this.type
Sets a parameter in the embedded param map.
Sets a parameter in the embedded param map.
- Definition Classes
- Params
-
def
setBlockSize(value: Int): ALSModel.this.type
Set block size for stacking input data in matrices.
Set block size for stacking input data in matrices. Default is 4096.
- Annotations
- @Since( "3.0.0" )
-
def
setColdStartStrategy(value: String): ALSModel.this.type
- Annotations
- @Since( "2.2.0" )
-
final
def
setDefault(paramPairs: ParamPair[_]*): ALSModel.this.type
Sets default values for a list of params.
Sets default values for a list of params.
Note: Java developers should use the single-parameter
setDefault
. Annotating this with varargs can cause compilation failures due to a Scala compiler bug. See SPARK-9268.- paramPairs
a list of param pairs that specify params and their default values to set respectively. Make sure that the params are initialized before this method gets called.
- Attributes
- protected
- Definition Classes
- Params
-
final
def
setDefault[T](param: Param[T], value: T): ALSModel.this.type
Sets a default value for a param.
-
def
setItemCol(value: String): ALSModel.this.type
- Annotations
- @Since( "1.4.0" )
-
def
setParent(parent: Estimator[ALSModel]): ALSModel
Sets the parent of this model (Java API).
Sets the parent of this model (Java API).
- Definition Classes
- Model
-
def
setPredictionCol(value: String): ALSModel.this.type
- Annotations
- @Since( "1.3.0" )
-
def
setUserCol(value: String): ALSModel.this.type
- Annotations
- @Since( "1.4.0" )
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
-
def
toString(): String
- Definition Classes
- ALSModel → Identifiable → AnyRef → Any
- Annotations
- @Since( "3.0.0" )
-
def
transform(dataset: Dataset[_]): DataFrame
Transforms the input dataset.
Transforms the input dataset.
- Definition Classes
- ALSModel → Transformer
- Annotations
- @Since( "2.0.0" )
-
def
transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
Transforms the dataset with provided parameter map as additional parameters.
Transforms the dataset with provided parameter map as additional parameters.
- dataset
input dataset
- paramMap
additional parameters, overwrite embedded params
- returns
transformed dataset
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" )
-
def
transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
Transforms the dataset with optional parameters
Transforms the dataset with optional parameters
- dataset
input dataset
- firstParamPair
the first param pair, overwrite embedded params
- otherParamPairs
other param pairs, overwrite embedded params
- returns
transformed dataset
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" ) @varargs()
-
def
transformSchema(schema: StructType): StructType
Check transform validity and derive the output schema from the input schema.
Check transform validity and derive the output schema from the input schema.
We check validity for interactions between parameters during
transformSchema
and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled byParam.validate()
.Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
- Definition Classes
- ALSModel → PipelineStage
- Annotations
- @Since( "1.3.0" )
-
def
transformSchema(schema: StructType, logging: Boolean): StructType
:: DeveloperApi ::
:: DeveloperApi ::
Derives the output schema from the input schema and parameters, optionally with logging.
This should be optimistic. If it is unclear whether the schema will be valid, then it should be assumed valid until proven otherwise.
- Attributes
- protected
- Definition Classes
- PipelineStage
- Annotations
- @DeveloperApi()
-
val
uid: String
An immutable unique ID for the object and its derivatives.
An immutable unique ID for the object and its derivatives.
- Definition Classes
- ALSModel → Identifiable
- Annotations
- @Since( "1.4.0" )
-
val
userCol: Param[String]
Param for the column name for user ids.
Param for the column name for user ids. Ids must be integers. Other numeric types are supported for this column, but will be cast to integers as long as they fall within the integer value range. Default: "user"
- Definition Classes
- ALSModelParams
- val userFactors: DataFrame
-
final
def
wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
-
final
def
wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
def
write: MLWriter
Returns an
MLWriter
instance for this ML instance.Returns an
MLWriter
instance for this ML instance.- Definition Classes
- ALSModel → MLWritable
- Annotations
- @Since( "1.6.0" )
Deprecated Value Members
-
def
finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( classOf[java.lang.Throwable] ) @Deprecated
- Deprecated
Inherited from MLWritable
Inherited from ALSModelParams
Inherited from HasBlockSize
Inherited from HasPredictionCol
Inherited from Transformer
Inherited from PipelineStage
Inherited from Logging
Inherited from Params
Inherited from Serializable
Inherited from Serializable
Inherited from Identifiable
Inherited from AnyRef
Inherited from Any
Parameters
A list of (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.
Members
Parameter setters
Parameter getters
(expert-only) Parameters
A list of advanced, expert-only (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.