org.apache.spark.mllib.feature

Word2Vec

class Word2Vec extends Serializable with Logging

:: Experimental :: Word2Vec creates vector representation of words in a text corpus. The algorithm first constructs a vocabulary from the corpus and then learns vector representation of words in the vocabulary. The vector representation can be used as features in natural language processing and machine learning algorithms.

We used skip-gram model in our implementation and hierarchical softmax method to train the model. The variable names in the implementation matches the original C implementation.

For original C implementation, see https://code.google.com/p/word2vec/ For research papers, see Efficient Estimation of Word Representations in Vector Space and Distributed Representations of Words and Phrases and their Compositionality.

Annotations
@Experimental()
Linear Supertypes
Logging, Serializable, Serializable, AnyRef, Any
Ordering
  1. Alphabetic
  2. By inheritance
Inherited
  1. Word2Vec
  2. Logging
  3. Serializable
  4. Serializable
  5. AnyRef
  6. Any
  1. Hide All
  2. Show all
Learn more about member selection
Visibility
  1. Public
  2. All

Instance Constructors

  1. new Word2Vec()

Value Members

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

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

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  7. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  10. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  11. def fit[S <: Iterable[String]](dataset: JavaRDD[S]): Word2VecModel

    Computes the vector representation of each word in vocabulary (Java version).

    Computes the vector representation of each word in vocabulary (Java version).

    dataset

    a JavaRDD of words

    returns

    a Word2VecModel

  12. def fit[S <: Iterable[String]](dataset: RDD[S]): Word2VecModel

    Computes the vector representation of each word in vocabulary.

    Computes the vector representation of each word in vocabulary.

    dataset

    an RDD of words

    returns

    a Word2VecModel

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

    Definition Classes
    AnyRef → Any
  14. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  15. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  16. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging
  17. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging
  18. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  19. def logDebug(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  20. def logError(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  21. def logError(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  22. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  23. def logInfo(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  24. def logName: String

    Attributes
    protected
    Definition Classes
    Logging
  25. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  26. def logTrace(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  27. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  28. def logWarning(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  29. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  30. final def notify(): Unit

    Definition Classes
    AnyRef
  31. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  32. def setLearningRate(learningRate: Double): Word2Vec.this.type

    Sets initial learning rate (default: 0.

    Sets initial learning rate (default: 0.025).

  33. def setNumIterations(numIterations: Int): Word2Vec.this.type

    Sets number of iterations (default: 1), which should be smaller than or equal to number of partitions.

  34. def setNumPartitions(numPartitions: Int): Word2Vec.this.type

    Sets number of partitions (default: 1).

    Sets number of partitions (default: 1). Use a small number for accuracy.

  35. def setSeed(seed: Long): Word2Vec.this.type

    Sets random seed (default: a random long integer).

  36. def setVectorSize(vectorSize: Int): Word2Vec.this.type

    Sets vector size (default: 100).

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

    Definition Classes
    AnyRef
  38. def toString(): String

    Definition Classes
    AnyRef → Any
  39. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  40. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  41. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Logging

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped