LocalFileSystemPersistentModel

This trait is a convenience helper for persisting your model to the local filesystem. This trait and LocalFileSystemPersistentModelLoader contain concrete implementation and need not be implemented.

The underlying implementation is Utils.save.

class MyModel extends LocalFileSystemPersistentModel[MyParams] {
  ...
}

object MyModel extends LocalFileSystemPersistentModelLoader[MyParams, MyModel] {
  ...
}

AP: Algorithm parameters class.

See also: LocalFileSystemPersistentModelLoader

Linear Supertypes

PersistentModel[AP], AnyRef, Any

Known Subclasses

IFSPersistentModel

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
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 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
def save(id: String, params: AP, sc: SparkContext): Boolean

Save the model to some persistent storage.
Save the model to some persistent storage.
This method should return true if the model has been saved successfully so that PredictionIO knows that it can be restored later during deployment. This method should return false if the model cannot be saved (or should not be saved due to configuration) so that PredictionIO will re-train the model during deployment. All arguments of this method are provided by automatically by PredictionIO.
id
ID of the run that trained this model.
params
Algorithm parameters that were used to train this model.
sc
An Apache Spark context.

Definition Classes
LocalFileSystemPersistentModel → PersistentModel
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
AnyRef → Any
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 Doc: package controller

trait LocalFileSystemPersistentModel[AP <: Params] extends PersistentModel[AP]

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

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

def save(id: String, params: AP, sc: SparkContext): Boolean

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

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from PersistentModel[AP]

Inherited from AnyRef

Inherited from Any

Ungrouped