Packages

class KNN extends Estimator[KNNModel] with KNNParams with DefaultParamsWritable with OptimizedKNNFitting with SynapseMLLogging

Linear Supertypes
OptimizedKNNFitting, SynapseMLLogging, DefaultParamsWritable, MLWritable, KNNParams, HasOutputCol, Wrappable, RWrappable, PythonWrappable, BaseWrappable, HasFeaturesCol, Estimator[KNNModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. KNN
  2. OptimizedKNNFitting
  3. SynapseMLLogging
  4. DefaultParamsWritable
  5. MLWritable
  6. KNNParams
  7. HasOutputCol
  8. Wrappable
  9. RWrappable
  10. PythonWrappable
  11. BaseWrappable
  12. HasFeaturesCol
  13. Estimator
  14. PipelineStage
  15. Logging
  16. Params
  17. Serializable
  18. Serializable
  19. Identifiable
  20. AnyRef
  21. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new KNN()
  2. new KNN(uid: String)

Value Members

  1. final def clear(param: Param[_]): KNN.this.type
    Definition Classes
    Params
  2. def copy(extra: ParamMap): Estimator[KNNModel]
    Definition Classes
    KNN → Estimator → PipelineStage → Params
  3. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  4. def explainParams(): String
    Definition Classes
    Params
  5. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  6. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  7. val featuresCol: Param[String]

    The name of the features column

    The name of the features column

    Definition Classes
    HasFeaturesCol
  8. def fit(dataset: Dataset[_]): KNNModel
    Definition Classes
    KNN → Estimator
  9. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[KNNModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  10. def fit(dataset: Dataset[_], paramMap: ParamMap): KNNModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  11. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): KNNModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  12. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  13. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  14. def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  15. def getK: Int
    Definition Classes
    KNNParams
  16. def getLeafSize: Int
    Definition Classes
    KNNParams
  17. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  18. def getOutputCol: String

    Definition Classes
    HasOutputCol
  19. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  20. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  21. def getValuesCol: String
    Definition Classes
    KNNParams
  22. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  23. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  24. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  25. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  26. val k: IntParam
    Definition Classes
    KNNParams
  27. val leafSize: IntParam
    Definition Classes
    KNNParams
  28. def logClass(featureName: String): Unit
    Definition Classes
    SynapseMLLogging
  29. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  30. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  31. def logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
    Definition Classes
    SynapseMLLogging
  32. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  33. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  34. val outputCol: Param[String]

    The name of the output column

    The name of the output column

    Definition Classes
    HasOutputCol
  35. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  36. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  37. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  38. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  39. final def set[T](param: Param[T], value: T): KNN.this.type
    Definition Classes
    Params
  40. def setFeaturesCol(value: String): KNN.this.type

    Definition Classes
    HasFeaturesCol
  41. def setK(v: Int): KNN.this.type
    Definition Classes
    KNNParams
  42. def setLeafSize(v: Int): KNN.this.type
    Definition Classes
    KNNParams
  43. def setOutputCol(value: String): KNN.this.type

    Definition Classes
    HasOutputCol
  44. def setValuesCol(v: String): KNN.this.type
    Definition Classes
    KNNParams
  45. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  46. def transformSchema(schema: StructType): StructType
    Definition Classes
    KNN → PipelineStage
  47. val uid: String
    Definition Classes
    KNNSynapseMLLogging → Identifiable
  48. val valuesCol: Param[String]
    Definition Classes
    KNNParams
  49. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable