Engine

Type Members

class DataSourceMap[TD, EI, Q, A] extends AnyRef

Helper class to accept either a single data source, or a map of data sources, with a companion object providing implicit conversions, so using this class directly is not necessary.
Helper class to accept either a single data source, or a map of data sources, with a companion object providing implicit conversions, so using this class directly is not necessary.
TD
Training data class
EI
Evaluation information class
Q
Input query class
A
Actual result class
class PreparatorMap[TD, PD] extends AnyRef

Helper class to accept either a single preparator, or a map of preparators, with a companion object providing implicit conversions, so using this class directly is not necessary.
Helper class to accept either a single preparator, or a map of preparators, with a companion object providing implicit conversions, so using this class directly is not necessary.
TD
Training data class
PD
Prepared data class
class ServingMap[Q, P] extends AnyRef

Helper class to accept either a single serving, or a map of serving, with a companion object providing implicit conversions, so using this class directly is not necessary.
Helper class to accept either a single serving, or a map of serving, with a companion object providing implicit conversions, so using this class directly is not necessary.
Q
Input query class
P
Predicted result class

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
object DataSourceMap

Companion object providing implicit conversions, so using this directly is not necessary.
object PreparatorMap

Companion object providing implicit conversions, so using this directly is not necessary.
object ServingMap

Companion object providing implicit conversions, so using this directly is not necessary.
def apply[TD, EI, PD, Q, P, A](dataSourceMap: DataSourceMap[TD, EI, Q, A], preparatorMap: PreparatorMap[TD, PD], algorithmClassMap: Map[String, Class[_ <: BaseAlgorithm[PD, _, Q, P]]], servingMap: ServingMap[Q, P]): Engine[TD, EI, PD, Q, P, A]

Convenient method for returning an instance of Engine.
Convenient method for returning an instance of Engine.
TD
Training data class
EI
Evaluation information class
PD
Prepared data class
Q
Input query class
P
Predicted result class
A
Actual result class
dataSourceMap
Accepts either an instance of Class of the data source, or a Map of data source classes (implicitly converted to DataSourceMap.
preparatorMap
Accepts either an instance of Class of the preparator, or a Map of preparator classes (implicitly converted to PreparatorMap.
algorithmClassMap
Accepts a Map of algorithm classes.
servingMap
Accepts either an instance of Class of the serving, or a Map of serving classes (implicitly converted to ServingMap.
returns
An instance of Engine
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def eval[TD, PD, Q, P, A, EI](sc: SparkContext, dataSource: BaseDataSource[TD, EI, Q, A], preparator: BasePreparator[TD, PD], algorithmList: Seq[BaseAlgorithm[PD, _, Q, P]], serving: BaseServing[Q, P]): Seq[(EI, RDD[(Q, P, A)])]

Provides concrete implementation of evaluation for Engine.
Provides concrete implementation of evaluation for Engine.
TD
Training data class
PD
Prepared data class
Q
Input query class
P
Predicted result class
A
Actual result class
EI
Evaluation information class
sc
An instance of SparkContext
dataSource
An instance of data source
preparator
An instance of preparator
algorithmList
A list of algorithm instances
serving
An instance of serving
returns
A list of evaluation information, RDD of query, predicted result, and actual result tuple tuple.
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def hashCode(): Int

Definition Classes
AnyRef → Any
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
AnyRef → Any
def train[TD, PD, Q](sc: SparkContext, dataSource: BaseDataSource[TD, _, Q, _], preparator: BasePreparator[TD, PD], algorithmList: Seq[BaseAlgorithm[PD, _, Q, _]], params: WorkflowParams): Seq[Any]

Provides concrete implementation of training for Engine.
Provides concrete implementation of training for Engine.
TD
Training data class
PD
Prepared data class
Q
Input query class
sc
An instance of SparkContext
dataSource
An instance of data source
preparator
An instance of preparator
algorithmList
A list of algorithm instances
params
An instance of WorkflowParams that controls the training process.
returns
A list of trained models
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

Related Docs: class Engine | package controller

object Engine extends Serializable

Type Members

class DataSourceMap[TD, EI, Q, A] extends AnyRef

class PreparatorMap[TD, PD] extends AnyRef

class ServingMap[Q, P] extends AnyRef

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

object DataSourceMap

object PreparatorMap

object ServingMap

def apply[TD, EI, PD, Q, P, A](dataSourceMap: DataSourceMap[TD, EI, Q, A], preparatorMap: PreparatorMap[TD, PD], algorithmClassMap: Map[String, Class[_ <: BaseAlgorithm[PD, _, Q, P]]], servingMap: ServingMap[Q, P]): Engine[TD, EI, PD, Q, P, A]

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def eval[TD, PD, Q, P, A, EI](sc: SparkContext, dataSource: BaseDataSource[TD, EI, Q, A], preparator: BasePreparator[TD, PD], algorithmList: Seq[BaseAlgorithm[PD, _, Q, P]], serving: BaseServing[Q, P]): Seq[(EI, RDD[(Q, P, A)])]

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

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

def toString(): String

def train[TD, PD, Q](sc: SparkContext, dataSource: BaseDataSource[TD, _, Q, _], preparator: BasePreparator[TD, PD], algorithmList: Seq[BaseAlgorithm[PD, _, Q, _]], params: WorkflowParams): Seq[Any]

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped