Trait

io.github.mandar2812.dynaml.models

LinearModel

Related Doc: package models

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trait LinearModel[T, P, Q, R, S] extends ParameterizedLearner[T, P, Q, R, S]

Represents skeleton of a Linear Model.

T

The underlying type of the data structure ex. Gremlin, Neo4j, Spark RDD etc

P

A Vector/Matrix of Doubles

Q

A Vector/Matrix representing the features of a point

R

The type of the output of the predictive model i.e. A Real Number or a Vector of outputs.

S

The type of the data containing the features and label.

Linear Supertypes
ParameterizedLearner[T, P, Q, R, S], Model[T, Q, R], AnyRef, Any
Known Subclasses
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Inherited
  1. LinearModel
  2. ParameterizedLearner
  3. Model
  4. AnyRef
  5. Any
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Abstract Value Members

  1. abstract def clearParameters(): Unit

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  2. abstract val g: T

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    The training data

    The training data

    Attributes
    protected
    Definition Classes
    Model
  3. abstract def initParams(): P

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    Definition Classes
    ParameterizedLearner
  4. abstract def learn(): Unit

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    Learn the parameters of the model.

    Learn the parameters of the model.

    Definition Classes
    ParameterizedLearner
  5. abstract val optimizer: RegularizedOptimizer[P, Q, R, S]

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    Attributes
    protected
    Definition Classes
    ParameterizedLearner
  6. abstract val params: P

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    Attributes
    protected
    Definition Classes
    ParameterizedLearner
  7. abstract def predict(point: Q): R

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    Predict the value of the target variable given a point.

    Predict the value of the target variable given a point.

    Definition Classes
    Model

Concrete Value Members

  1. final def !=(arg0: Any): Boolean

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

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

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    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  5. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  6. def data: T

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    Definition Classes
    Model
  7. final def eq(arg0: AnyRef): Boolean

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

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    Definition Classes
    AnyRef → Any
  9. var featureMap: (Q) ⇒ Q

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    The non linear feature mapping implicitly defined by the kernel applied, this is initialized to an identity map.

  10. def finalize(): Unit

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

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    Definition Classes
    AnyRef → Any
  12. def hashCode(): Int

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

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

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    Definition Classes
    AnyRef
  15. final def notify(): Unit

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    Definition Classes
    AnyRef
  16. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  17. def parameters(): P

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    Get the value of the parameters of the model.

    Get the value of the parameters of the model.

    Definition Classes
    ParameterizedLearner
  18. def setBatchFraction(f: Double): LinearModel.this.type

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    Definition Classes
    ParameterizedLearner
  19. def setLearningRate(alpha: Double): LinearModel.this.type

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    Definition Classes
    ParameterizedLearner
  20. def setMaxIterations(i: Int): LinearModel.this.type

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    Definition Classes
    ParameterizedLearner
  21. def setRegParam(r: Double): LinearModel.this.type

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    Definition Classes
    ParameterizedLearner
  22. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  23. def toString(): String

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    Definition Classes
    AnyRef → Any
  24. def updateParameters(param: P): Unit

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    Definition Classes
    ParameterizedLearner
  25. final def wait(): Unit

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

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from ParameterizedLearner[T, P, Q, R, S]

Inherited from Model[T, Q, R]

Inherited from AnyRef

Inherited from Any

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