CategoricalDistibutionModel

A model representing a categorical distribution. This will return values with the probabilities prescribed by the distribution parameter. For information on categorical distributions, check out Wikipedia's page.

A: model input type
B: model output type
modelId: An id with which to identify this model
features: features whose values are fed to the distribution. These features are functions of the input.
distribution: A distribution parametrized by a sequence of probabilities, that takes a sequence of values and produces a hash that is used as the randomness with which to choose one of the labels.
labels: the values that can returned by this model (with the probabilities described by the distribution)
missingOk: Whether to allow missing data defaults to false). When this is set to false and missing data ( scala.None) is produced by one of the features, the model will result in an error.

Linear Supertypes

Serializable, Serializable, Product, Equals, SubmodelBase[U, N, A, B], Model[A, B], (A) ⇒ B, Submodel[N, A, B], Closeable, AutoCloseable, Identifiable[ModelIdentity], AnyRef, Any

Instance Constructors

new CategoricalDistibutionModel(modelId: ModelIdentity, features: Seq[GenAggFunc[A, Any]], distribution: HashedCategoricalDistribution, labels: IndexedSeq[N], auditor: Auditor[U, N, B], missingOk: Boolean = false)

modelId
An id with which to identify this model
features
features whose values are fed to the distribution. These features are functions of the input.
distribution
A distribution parametrized by a sequence of probabilities, that takes a sequence of values and produces a hash that is used as the randomness with which to choose one of the labels.
labels
the values that can returned by this model (with the probabilities described by the distribution)
missingOk
Whether to allow missing data defaults to false). When this is set to false and missing data ( scala.None) is produced by one of the features, the model will result in an error.

Value Members

final def !=(arg0: AnyRef): Boolean

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

Definition Classes
Any
final def ##(): Int

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

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

Definition Classes
Any
def andThen[A](g: (B) ⇒ A): (A) ⇒ A

Definition Classes
Function1
Annotations
@unspecialized()
final def apply(a: A): B

Definition Classes
SubmodelBase → Function1
final def asInstanceOf[T0]: T0

Definition Classes
Any
val auditor: Auditor[U, N, B]

Definition Classes
CategoricalDistibutionModel → SubmodelBase
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
def close(): Unit

Definition Classes
SubmodelBase → Closeable → AutoCloseable
def compose[A](g: (A) ⇒ A): (A) ⇒ B

Definition Classes
Function1
Annotations
@unspecialized()
val distribution: HashedCategoricalDistribution

A distribution parametrized by a sequence of probabilities, that takes a sequence of values and produces a hash that is used as the randomness with which to choose one of the labels.
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def failure(errorMsgs: ⇒ Seq[String] = Nil, missingVarNames: ⇒ Set[String] = Set.empty, subvalues: Seq[U] = Nil): Subvalue[B, N]

Attributes
protected[this]
Definition Classes
SubmodelBase
val features: Seq[GenAggFunc[A, Any]]

features whose values are fed to the distribution.
features whose values are fed to the distribution. These features are functions of the input.
def finalize(): Unit

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

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

Definition Classes
Any
val labels: IndexedSeq[N]

the values that can returned by this model (with the probabilities described by the distribution)
val missingOk: Boolean

Whether to allow missing data defaults to false).
Whether to allow missing data defaults to false). When this is set to false and missing data ( scala.None) is produced by one of the features, the model will result in an error.
val modelId: ModelIdentity

An id with which to identify this model
An id with which to identify this model

Definition Classes
CategoricalDistibutionModel → Identifiable
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def subvalue(a: A): Subvalue[B, N]

"Randomly" but idempotently pick a label based on the probabilities in the distribution.
"Randomly" but idempotently pick a label based on the probabilities in the distribution.
a
input from which features are extracted. These features are then hashed to produce a value.
returns
a positive value i if node i should be selected. May return a negative value in which case processErrorAt should be called with the value returned.

Definition Classes
CategoricalDistibutionModel → Submodel
def success(naturalValue: N, errorMsgs: ⇒ Seq[String] = Nil, missingVarNames: ⇒ Set[String] = Set.empty, subvalues: Seq[U] = Nil, prob: ⇒ Option[Float] = None): Subvalue[B, N]

Attributes
protected[this]
Definition Classes
SubmodelBase
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
CategoricalDistibutionModel → Function1 → 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( ... )

Instance Constructors

new CategoricalDistibutionModel(modelId: ModelIdentity, features: Seq[GenAggFunc[A, Any]], distribution: HashedCategoricalDistribution, labels: IndexedSeq[N], auditor: Auditor[U, N, B], missingOk: Boolean = false)

Value Members

final def !=(arg0: AnyRef): Boolean

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: AnyRef): Boolean

final def ==(arg0: Any): Boolean

def andThen[A](g: (B) ⇒ A): (A) ⇒ A

final def apply(a: A): B

final def asInstanceOf[T0]: T0

val auditor: Auditor[U, N, B]

def clone(): AnyRef

def close(): Unit

def compose[A](g: (A) ⇒ A): (A) ⇒ B

val distribution: HashedCategoricalDistribution

final def eq(arg0: AnyRef): Boolean

def failure(errorMsgs: ⇒ Seq[String] = Nil, missingVarNames: ⇒ Set[String] = Set.empty, subvalues: Seq[U] = Nil): Subvalue[B, N]

val features: Seq[GenAggFunc[A, Any]]

def finalize(): Unit

final def getClass(): Class[_]

final def isInstanceOf[T0]: Boolean

val labels: IndexedSeq[N]

val missingOk: Boolean

val modelId: ModelIdentity

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def subvalue(a: A): Subvalue[B, N]

def success(naturalValue: N, errorMsgs: ⇒ Seq[String] = Nil, missingVarNames: ⇒ Set[String] = Set.empty, subvalues: Seq[U] = Nil, prob: ⇒ Option[Float] = None): Subvalue[B, N]

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 Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from SubmodelBase[U, N, A, B]

Inherited from Model[A, B]

Inherited from (A) ⇒ B

Inherited from Submodel[N, A, B]

Inherited from Closeable

Inherited from AutoCloseable

Inherited from Identifiable[ModelIdentity]

Inherited from AnyRef

Inherited from Any

Ungrouped