LinearRegressionModel

Value Members

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

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

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3. final def ##(): Int

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4. final def ==(arg0: AnyRef): Boolean

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

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6. final def asInstanceOf[T0]: T0

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7. def clone(): AnyRef

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   protected[java.lang]

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

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9. def equals(arg0: Any): Boolean

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10. def finalize(): Unit

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    protected[java.lang]

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

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12. def hashCode(): Int

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13. val intercept: Double

    Intercept computed for this model.

    Intercept computed for this model.

    Definition Classes

    LinearRegressionModel → GeneralizedLinearModel

14. final def isInstanceOf[T0]: Boolean

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

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16. final def notify(): Unit

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17. final def notifyAll(): Unit

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18. def predict(testData: JavaRDD[Vector]): JavaRDD[Double]

    Predict values for examples stored in a JavaRDD.

    Predict values for examples stored in a JavaRDD.

    testData

    JavaRDD representing data points to be predicted

    returns

    a JavaRDD[java.lang.Double] where each entry contains the corresponding prediction

    Definition Classes

    RegressionModel

19. def predict(testData: Vector): Double

    Predict values for a single data point using the model trained.

    Predict values for a single data point using the model trained.

    testData

    array representing a single data point

    returns

    Double prediction from the trained model

    Definition Classes

    GeneralizedLinearModel

20. def predict(testData: RDD[Vector]): RDD[Double]

    Predict values for the given data set using the model trained.

    Predict values for the given data set using the model trained.

    testData

    RDD representing data points to be predicted

    returns

    RDD[Double] where each entry contains the corresponding prediction

    Definition Classes

    GeneralizedLinearModel

21. def predictPoint(dataMatrix: Vector, weightMatrix: Vector, intercept: Double): Double

    Predict the result given a data point and the weights learned.

    Predict the result given a data point and the weights learned.

    dataMatrix

    Row vector containing the features for this data point

    weightMatrix

    Column vector containing the weights of the model

    intercept

    Intercept of the model.

    Attributes

    protected

    Definition Classes

    LinearRegressionModel → GeneralizedLinearModel

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

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23. def toString(): String

    Definition Classes

    GeneralizedLinearModel → AnyRef → Any

24. final def wait(): Unit

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

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

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27. val weights: Vector

    Weights computed for every feature.

    Weights computed for every feature.

    Definition Classes

    LinearRegressionModel → GeneralizedLinearModel