Trait

org.apache.spark.ml.classification

LogisticRegressionTrainingSummary

Related Doc: package classification

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sealed trait LogisticRegressionTrainingSummary extends LogisticRegressionSummary

Abstraction for multinomial Logistic Regression Training results. Currently, the training summary ignores the training weights except for the objective trace.

Source
LogisticRegression.scala
Linear Supertypes
LogisticRegressionSummary, Serializable, Serializable, AnyRef, Any
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  1. LogisticRegressionTrainingSummary
  2. LogisticRegressionSummary
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Abstract Value Members

  1. abstract def featuresCol: String

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    Field in "predictions" which gives the features of each instance as a vector.

    Field in "predictions" which gives the features of each instance as a vector.

    Definition Classes
    LogisticRegressionSummary
  2. abstract def labelCol: String

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    Field in "predictions" which gives the true label of each instance (if available).

    Field in "predictions" which gives the true label of each instance (if available).

    Definition Classes
    LogisticRegressionSummary
  3. abstract def objectiveHistory: Array[Double]

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    objective function (scaled loss + regularization) at each iteration.

  4. abstract def predictions: DataFrame

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    Dataframe output by the model's transform method.

    Dataframe output by the model's transform method.

    Definition Classes
    LogisticRegressionSummary
  5. abstract def probabilityCol: String

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    Field in "predictions" which gives the probability of each class as a vector.

    Field in "predictions" which gives the probability of each class as a vector.

    Definition Classes
    LogisticRegressionSummary

Concrete Value Members

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

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. final def eq(arg0: AnyRef): Boolean

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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  9. final def getClass(): Class[_]

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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  12. final def ne(arg0: AnyRef): Boolean

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  13. final def notify(): Unit

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  14. final def notifyAll(): Unit

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

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  16. def toString(): String

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  17. def totalIterations: Int

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    Number of training iterations until termination

  18. final def wait(): Unit

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

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  20. final def wait(arg0: Long): Unit

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Inherited from LogisticRegressionSummary

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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