Spark 3.5.5 ScalaDoc - org.apache.spark.mllib.classification.LogisticRegressionModel (original) (raw)

class LogisticRegressionModel extends GeneralizedLinearModel with ClassificationModel with Serializable with Saveable with PMMLExportable

Ordering

  1. Alphabetic
  2. By Inheritance

Inherited

  1. LogisticRegressionModel

  2. PMMLExportable

  3. Saveable

  4. ClassificationModel

  5. GeneralizedLinearModel

  6. Serializable

  7. Serializable

  8. AnyRef

  9. Any

  10. Hide All

  11. Show All

Instance Constructors

  1. new LogisticRegressionModel(weights: Vector, intercept: Double)
  2. new LogisticRegressionModel(weights: Vector, intercept: Double, numFeatures: Int, numClasses: Int)

Value Members

  1. final def !=(arg0: Any): Boolean
  2. final def ##(): Int
  3. final def ==(arg0: Any): Boolean
  4. final def asInstanceOf[T0]: T0
  5. def clearThreshold(): LogisticRegressionModel.this.type
  6. def clone(): AnyRef
  7. final def eq(arg0: AnyRef): Boolean
  8. def equals(arg0: Any): Boolean
  9. def finalize(): Unit
  10. final def getClass(): Class[_]
  11. def getThreshold: Option[Double]
  12. def hashCode(): Int
  13. val intercept: Double
  14. final def isInstanceOf[T0]: Boolean
  15. final def ne(arg0: AnyRef): Boolean
  16. final def notify(): Unit
  17. final def notifyAll(): Unit
  18. val numClasses: Int
  19. val numFeatures: Int
  20. def predict(testData: JavaRDD[Vector]): JavaRDD[Double]
  21. def predict(testData: Vector): Double
  22. def predict(testData: RDD[Vector]): RDD[Double]
  23. def predictPoint(dataMatrix: Vector, weightMatrix: Vector, intercept: Double): Double
  24. def save(sc: SparkContext, path: String): Unit
  25. def setThreshold(threshold: Double): LogisticRegressionModel.this.type
  26. final def synchronized[T0](arg0: ⇒ T0): T0
  27. def toPMML(): String
  28. def toPMML(outputStream: OutputStream): Unit
  29. def toPMML(sc: SparkContext, path: String): Unit
  30. def toPMML(localPath: String): Unit
  31. def toString(): String
  32. final def wait(): Unit
  33. final def wait(arg0: Long, arg1: Int): Unit
  34. final def wait(arg0: Long): Unit
  35. val weights: Vector

Ungrouped