Object

org.apache.spark.mllib.linalg

Vectors

Related Doc: package linalg

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object Vectors

Factory methods for org.apache.spark.mllib.linalg.Vector. We don't use the name Vector because Scala imports scala.collection.immutable.Vector by default.

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@Since( "1.0.0" )
Source
Vectors.scala
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  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. def dense(values: Array[Double]): Vector

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    Creates a dense vector from a double array.

    Creates a dense vector from a double array.

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    @Since( "1.0.0" )
  7. def dense(firstValue: Double, otherValues: Double*): Vector

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    Creates a dense vector from its values.

    Creates a dense vector from its values.

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    @Since( "1.0.0" ) @varargs()
  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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  11. def fromJson(json: String): Vector

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    Parses the JSON representation of a vector into a Vector.

    Parses the JSON representation of a vector into a Vector.

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    @Since( "1.6.0" )
  12. def fromML(v: ml.linalg.Vector): Vector

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    Convert new linalg type to spark.mllib type.

    Convert new linalg type to spark.mllib type. Light copy; only copies references

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    @Since( "2.0.0" )
  13. final def getClass(): Class[_]

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  14. def hashCode(): Int

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  15. final def isInstanceOf[T0]: Boolean

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

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  17. def norm(vector: Vector, p: Double): Double

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    Returns the p-norm of this vector.

    Returns the p-norm of this vector.

    vector

    input vector.

    p

    norm.

    returns

    norm in Lp space.

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    @Since( "1.3.0" )
  18. final def notify(): Unit

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  19. final def notifyAll(): Unit

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  20. def parse(s: String): Vector

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    Parses a string resulted from Vector.toString into a Vector.

    Parses a string resulted from Vector.toString into a Vector.

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    @Since( "1.1.0" )
  21. def sparse(size: Int, elements: Iterable[(Integer, Double)]): Vector

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    Creates a sparse vector using unordered (index, value) pairs in a Java friendly way.

    Creates a sparse vector using unordered (index, value) pairs in a Java friendly way.

    size

    vector size.

    elements

    vector elements in (index, value) pairs.

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    @Since( "1.0.0" )
  22. def sparse(size: Int, elements: Seq[(Int, Double)]): Vector

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    Creates a sparse vector using unordered (index, value) pairs.

    Creates a sparse vector using unordered (index, value) pairs.

    size

    vector size.

    elements

    vector elements in (index, value) pairs.

    Annotations
    @Since( "1.0.0" )
  23. def sparse(size: Int, indices: Array[Int], values: Array[Double]): Vector

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    Creates a sparse vector providing its index array and value array.

    Creates a sparse vector providing its index array and value array.

    size

    vector size.

    indices

    index array, must be strictly increasing.

    values

    value array, must have the same length as indices.

    Annotations
    @Since( "1.0.0" )
  24. def sqdist(v1: Vector, v2: Vector): Double

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    Returns the squared distance between two Vectors.

    Returns the squared distance between two Vectors.

    v1

    first Vector.

    v2

    second Vector.

    returns

    squared distance between two Vectors.

    Annotations
    @Since( "1.3.0" )
  25. final def synchronized[T0](arg0: ⇒ T0): T0

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  26. def toString(): String

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  27. final def wait(): Unit

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

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

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  30. def zeros(size: Int): Vector

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    Creates a vector of all zeros.

    Creates a vector of all zeros.

    size

    vector size

    returns

    a zero vector

    Annotations
    @Since( "1.1.0" )

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