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object RecommenderTest extends App with Recommender

The RecommenderTest is used to test the Recommender trait. > runMain scalation.analytics.recommender.RecommenderTest

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Recommender, App, DelayedInit, AnyRef, Any
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Inherited
  1. RecommenderTest
  2. Recommender
  3. App
  4. DelayedInit
  5. AnyRef
  6. Any
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Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. def args: Array[String]
    Attributes
    protected
    Definition Classes
    App
    Annotations
    @deprecatedOverriding( "args should not be overridden" , "2.11.0" )
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  7. def crossValidate(tester: MatrixD): Unit

    Phase 2: Cross validate the final predictions against the test dataset.

    Phase 2: Cross validate the final predictions against the test dataset.

    tester

    testing data matrix

    Definition Classes
    Recommender
  8. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  10. def error_metrics(input: MatrixI): Unit

    Phase 1: Print MAE and RMSE metrics based on the final predictions for the test dataset.

    Phase 1: Print MAE and RMSE metrics based on the final predictions for the test dataset.

    input

    the test portion of the original 4-column input matrix

    Definition Classes
    Recommender
  11. val executionStart: Long
    Definition Classes
    App
    Annotations
    @deprecatedOverriding( ... , "2.11.0" )
  12. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  13. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  14. def getStats: Array[Statistic]

    Return the variables for the statistics vectors.

    Return the variables for the statistics vectors.

    Definition Classes
    Recommender
  15. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  16. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  17. def main(args: Array[String]): Unit
    Definition Classes
    App
    Annotations
    @deprecatedOverriding( "main should not be overridden" , "2.11.0" )
  18. def makeRatings(input: MatrixI, m: Int, n: Int): MatrixD

    Convert an original 4-column 'input' integer matrix (i, j, value, timestamp) into a two-dimensional 'ratings' double matrix with 'm' rows and 'n' columns.

    Convert an original 4-column 'input' integer matrix (i, j, value, timestamp) into a two-dimensional 'ratings' double matrix with 'm' rows and 'n' columns. The 'input' matrix has type MatrixI, while the 'ratings' matrix has type MatrixD.

    input

    the original 4-column input data matrix containing ratings, e.g., from a file

    m

    the number of rows for the ratings matrix

    n

    the number of columns for the ratings matrix

    Definition Classes
    Recommender
  19. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  20. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  21. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  22. def rate(i: Int, j: Int): Double

    Return the final rating for a given '(i, j)' cell, e.g., (user, item).

    Return the final rating for a given '(i, j)' cell, e.g., (user, item).

    i

    the ith row, e.g., user

    j

    the jth column, e.g., item

    Definition Classes
    RecommenderTest → Recommender
  23. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  24. def test(istart: Int, iend: Int, input: MatrixI): Unit

    Phase 3: Test the accuracy of the predictions and add it to the statistics vector.

    Phase 3: Test the accuracy of the predictions and add it to the statistics vector.

    istart

    the start point

    iend

    the end point

    input

    the original 4-column input matrix

    Definition Classes
    Recommender
  25. def toString(): String
    Definition Classes
    AnyRef → Any
  26. def topk(x: VectorD, k: Int): VectorI

    Return the indices of the 'k' largest values in vector 'x'.

    Return the indices of the 'k' largest values in vector 'x'. FIX - replace with more efficient top-k algorithm

    x

    the input vector

    k

    the number of values to be returned

    Definition Classes
    Recommender
  27. def topk2(x: VectorD, k: Int): Array[Int]

    Return the indices of the 'k' largest values in vector 'x'.

    Return the indices of the 'k' largest values in vector 'x'.

    x

    the input vector

    k

    the number of values to be returned

    Definition Classes
    Recommender
  28. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  29. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  30. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  31. val x: VectorD

Deprecated Value Members

  1. def delayedInit(body: ⇒ Unit): Unit
    Definition Classes
    App → DelayedInit
    Annotations
    @deprecated
    Deprecated

    (Since version 2.11.0) the delayedInit mechanism will disappear

Inherited from Recommender

Inherited from App

Inherited from DelayedInit

Inherited from AnyRef

Inherited from Any

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