Packages

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

Linear Supertypes
OptimizedKNNFitting, SynapseMLLogging, DefaultParamsWritable, MLWritable, KNNParams, HasOutputCol, Wrappable, DotnetWrappable, RWrappable, PythonWrappable, BaseWrappable, HasFeaturesCol, Estimator[KNNModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. KNN
  2. OptimizedKNNFitting
  3. SynapseMLLogging
  4. DefaultParamsWritable
  5. MLWritable
  6. KNNParams
  7. HasOutputCol
  8. Wrappable
  9. DotnetWrappable
  10. RWrappable
  11. PythonWrappable
  12. BaseWrappable
  13. HasFeaturesCol
  14. Estimator
  15. PipelineStage
  16. Logging
  17. Params
  18. Serializable
  19. Serializable
  20. Identifiable
  21. AnyRef
  22. Any
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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 dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  4. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  5. def explainParams(): String
    Definition Classes
    Params
  6. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  7. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  8. val featuresCol: Param[String]

    The name of the features column

    The name of the features column

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

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

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

    The name of the output column

    The name of the output column

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

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

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