HnswSimilarityModel

abstract def copy(extra: ParamMap): HnswSimilarityModel

abstract def getNumPartitions: Int

abstract def transform(dataset: Dataset[_]): DataFrame

abstract def transformSchema(schema: StructType): StructType

abstract val uid: String

abstract def write: MLWriter

final def !=(arg0: Any): Boolean

final def ##(): Int

final def $[T](param: Param[T]): T

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

final def clear(param: Param[_]): HnswSimilarityModel.this.type

def clone(): AnyRef

def copyValues[T <: Params](to: T, extra: ParamMap): T

final def defaultCopy[T <: Params](extra: ParamMap): T

final val ef: IntParam

Size of the dynamic list for the nearest neighbors (used during the search).

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

final val excludeSelf: BooleanParam

Param that indicates whether to not return the a candidate when it's identifier equals the query identifier Default: false

def explainParam(param: Param[_]): String

def explainParams(): String

final def extractParamMap(): ParamMap

final def extractParamMap(extra: ParamMap): ParamMap

final val featuresCol: Param[String]

def finalize(): Unit

final def get[T](param: Param[T]): Option[T]

final def getClass(): Class[_]

final def getDefault[T](param: Param[T]): Option[T]

final def getEf: Int

final def getExcludeSelf: Boolean

final def getFeaturesCol: String

final def getK: Int

final def getNumReplicas: Int

final def getOrDefault[T](param: Param[T]): T

final def getOutputFormat: String

final def getParallelism: Int

def getParam(paramName: String): Param[Any]

final def getPredictionCol: String

final def getQueryIdentifierCol: String

final def getQueryPartitionsCol: String

final def getSimilarityThreshold: Double

final def hasDefault[T](param: Param[T]): Boolean

def hasParam(paramName: String): Boolean

def hasParent: Boolean

def hashCode(): Int

def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

final def isDefined(param: Param[_]): Boolean

final def isInstanceOf[T0]: Boolean

final def isSet(param: Param[_]): Boolean

def isTraceEnabled(): Boolean

final val k: IntParam

Param for number of neighbors to find (> 0).

def log: Logger

def logDebug(msg: ⇒ String, throwable: Throwable): Unit

def logDebug(msg: ⇒ String): Unit

def logError(msg: ⇒ String, throwable: Throwable): Unit

def logError(msg: ⇒ String): Unit

def logInfo(msg: ⇒ String, throwable: Throwable): Unit

def logInfo(msg: ⇒ String): Unit

def logName: String

def logTrace(msg: ⇒ String, throwable: Throwable): Unit

def logTrace(msg: ⇒ String): Unit

def logWarning(msg: ⇒ String, throwable: Throwable): Unit

def logWarning(msg: ⇒ String): Unit

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

final val numReplicas: IntParam

Param that specifies the number of index replicas to create when querying the index.

final val outputFormat: Param[String]

Param for the output format to produce.

final val parallelism: IntParam

Param that specifies the number of threads to use.

lazy val params: Array[Param[_]]

var parent: Estimator[HnswSimilarityModel]

final val predictionCol: Param[String]

final val queryIdentifierCol: Param[String]

Param for the column name for the query identifier.

final val queryPartitionsCol: Param[String]

Param for the column name for the query partitions.

def save(path: String): Unit

final def set(paramPair: ParamPair[_]): HnswSimilarityModel.this.type

final def set(param: String, value: Any): HnswSimilarityModel.this.type

final def set[T](param: Param[T], value: T): HnswSimilarityModel.this.type

final def setDefault(paramPairs: ParamPair[_]*): HnswSimilarityModel.this.type

final def setDefault[T](param: Param[T], value: T): HnswSimilarityModel.this.type

def setEf(value: Int): HnswSimilarityModel.this.type

def setExcludeSelf(value: Boolean): HnswSimilarityModel.this.type

def setFeaturesCol(value: String): HnswSimilarityModel.this.type

def setK(value: Int): HnswSimilarityModel.this.type

def setNumReplicas(value: Int): HnswSimilarityModel.this.type

def setOutputFormat(value: String): HnswSimilarityModel.this.type

def setParallelism(value: Int): HnswSimilarityModel.this.type

def setParent(parent: Estimator[HnswSimilarityModel]): HnswSimilarityModel

def setPredictionCol(value: String): HnswSimilarityModel.this.type

def setQueryIdentifierCol(value: String): HnswSimilarityModel.this.type

def setQueryPartitionsCol(value: String): HnswSimilarityModel.this.type

def setSimilarityThreshold(value: Double): HnswSimilarityModel.this.type

final val similarityThreshold: DoubleParam

Param for the threshold value for inclusion.

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

def toString(): String

def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

def transformSchema(schema: StructType, logging: Boolean): StructType

def validateAndTransformSchema(schema: StructType, identifierDataType: DataType): StructType

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

final def wait(arg0: Long): Unit

final def wait(): Unit