Class/Object

com.tencent.angel.ml.matrixfactorization

MFModel

Related Docs: object MFModel | package matrixfactorization

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class MFModel extends MLModel

Matrix Factorization Model, consists item model and user model. Item model is a [#item, rank] matrix sotred on PS, each row represents an item. User model a UserVecs storage, each UserVec represents a user by a rank-dim vector. To save storage, we only cached items that appears in the local worker trainning data.

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MLModel, AnyRef, Any
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Instance Constructors

  1. new MFModel(conf: Configuration, _ctx: TaskContext = null)

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    conf

    : configuration of algorithm

    _ctx

    : context of running task

Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    AnyRef → Any

  4. def addPSModel(psModel: PSModel): MFModel.this.type

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    Definition Classes
    MLModel

  5. def addPSModel(name: String, psModel: PSModel): MFModel.this.type

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    Definition Classes
    MLModel

  6. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  7. def buildItems(items: HashMap[Int, ItemVec]): Unit

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    Build item vectors with local trainning data, onlu build items that appears in local trainning dataset

  8. def buildUsers(users: HashMap[Int, UserVec]): Unit

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    Buid user vectors with local trainning data, only build users that appears in local trainning dataset

  9. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  10. implicit def ctx: TaskContext

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    Definition Classes
    MLModel

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

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    Definition Classes
    AnyRef

  12. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  13. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

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    Definition Classes
    AnyRef → Any

  15. def getPSModel(name: String): PSModel

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    Definition Classes
    MLModel

  16. def getPSModels: Map[String, PSModel]

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    Definition Classes
    MLModel

  17. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  18. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  19. def itemMat: MatrixClient

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  20. def itemNum: Int

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  21. def items: HashMap[Int, ItemVec]

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

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    Definition Classes
    AnyRef

  23. final def notify(): Unit

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    Definition Classes
    AnyRef

  24. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  25. def predict(storage: DataBlock[LabeledData]): DataBlock[PredictResult]

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    Definition Classes
    MFModel → MLModel

  26. def rank: Int

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  27. def setLoadPath(conf: Configuration): MFModel.this.type

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    Definition Classes
    MLModel

  28. def setSavePath(conf: Configuration): MFModel.this.type

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    Definition Classes
    MLModel

  29. def setUsedItem(itemId: Int): Unit

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

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    Definition Classes
    AnyRef

  31. def toString(): String

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    Definition Classes
    AnyRef → Any

  32. def totalItemNum: Int

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  33. def usedItemIDs: Array[Byte]

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  34. def userNum: Int

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  35. def users: HashMap[Int, UserVec]

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  36. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from MLModel

Inherited from AnyRef

Inherited from Any

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