class ClassBalancerModel extends Model[ClassBalancerModel] with ComplexParamsWritable with Wrappable with HasInputCol with HasOutputCol with SynapseMLLogging
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$[T](param: Param[T]): T
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final
def
asInstanceOf[T0]: T0
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- val broadcastJoin: BooleanParam
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lazy val
classNameHelper: String
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final
def
clear(param: Param[_]): ClassBalancerModel.this.type
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def
clone(): AnyRef
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def
companionModelClassName: String
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def
copy(extra: ParamMap): ClassBalancerModel
- Definition Classes
- ClassBalancerModel → Model → Transformer → PipelineStage → Params
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def
copyValues[T <: Params](to: T, extra: ParamMap): T
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lazy val
copyrightLines: String
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final
def
defaultCopy[T <: Params](extra: ParamMap): T
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def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
explainParam(param: Param[_]): String
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def
explainParams(): String
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final
def
extractParamMap(): ParamMap
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final
def
extractParamMap(extra: ParamMap): ParamMap
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finalize(): Unit
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final
def
get[T](param: Param[T]): Option[T]
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final
def
getClass(): Class[_]
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final
def
getDefault[T](param: Param[T]): Option[T]
- Definition Classes
- Params
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def
getInputCol: String
- Definition Classes
- HasInputCol
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final
def
getOrDefault[T](param: Param[T]): T
- Definition Classes
- Params
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def
getOutputCol: String
- Definition Classes
- HasOutputCol
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def
getParam(paramName: String): Param[Any]
- Definition Classes
- Params
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def
getParamInfo(p: Param[_]): ParamInfo[_]
- Definition Classes
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def
getPayload(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], exception: Option[Exception]): Map[String, String]
- Attributes
- protected
- Definition Classes
- SynapseMLLogging
- def getWeights: DataFrame
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final
def
hasDefault[T](param: Param[T]): Boolean
- Definition Classes
- Params
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def
hasParam(paramName: String): Boolean
- Definition Classes
- Params
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def
hasParent: Boolean
- Definition Classes
- Model
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def
hashCode(): Int
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def
initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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def
initializeLogIfNecessary(isInterpreter: Boolean): Unit
- Attributes
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val
inputCol: Param[String]
The name of the input column
The name of the input column
- Definition Classes
- HasInputCol
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final
def
isDefined(param: Param[_]): Boolean
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final
def
isInstanceOf[T0]: Boolean
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def
isSet(param: Param[_]): Boolean
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def
isTraceEnabled(): Boolean
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def
log: Logger
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def
logBase(info: Map[String, String], featureName: Option[String]): Unit
- Attributes
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def
logBase(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], featureName: Option[String]): Unit
- Attributes
- protected
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def
logClass(featureName: String): Unit
- Definition Classes
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def
logDebug(msg: ⇒ String, throwable: Throwable): Unit
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def
logDebug(msg: ⇒ String): Unit
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def
logError(msg: ⇒ String, throwable: Throwable): Unit
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def
logError(msg: ⇒ String): Unit
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def
logErrorBase(methodName: String, e: Exception): Unit
- Attributes
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- Definition Classes
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def
logFit[T](f: ⇒ T, columns: Int): T
- Definition Classes
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def
logInfo(msg: ⇒ String, throwable: Throwable): Unit
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def
logInfo(msg: ⇒ String): Unit
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def
logName: String
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def
logTrace(msg: ⇒ String, throwable: Throwable): Unit
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def
logTrace(msg: ⇒ String): Unit
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def
logTransform[T](f: ⇒ T, columns: Int): T
- Definition Classes
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def
logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
- Definition Classes
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def
logWarning(msg: ⇒ String, throwable: Throwable): Unit
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def
logWarning(msg: ⇒ String): Unit
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- Logging
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def
makePyFile(conf: CodegenConfig): Unit
- Definition Classes
- PythonWrappable
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def
makeRFile(conf: CodegenConfig): Unit
- Definition Classes
- RWrappable
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final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
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final
def
notify(): Unit
- Definition Classes
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- @native()
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final
def
notifyAll(): Unit
- Definition Classes
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- Annotations
- @native()
-
val
outputCol: Param[String]
The name of the output column
The name of the output column
- Definition Classes
- HasOutputCol
-
lazy val
params: Array[Param[_]]
- Definition Classes
- Params
-
var
parent: Estimator[ClassBalancerModel]
- Definition Classes
- Model
-
def
pyAdditionalMethods: String
- Definition Classes
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lazy val
pyClassDoc: String
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lazy val
pyClassName: String
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def
pyExtraEstimatorImports: String
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def
pyExtraEstimatorMethods: String
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lazy val
pyInheritedClasses: Seq[String]
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def
pyInitFunc(): String
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lazy val
pyInternalWrapper: Boolean
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lazy val
pyObjectBaseClass: String
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def
pyParamArg[T](p: Param[T]): String
- Attributes
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def
pyParamDefault[T](p: Param[T]): Option[String]
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def
pyParamGetter(p: Param[_]): String
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def
pyParamSetter(p: Param[_]): String
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def
pyParamsArgs: String
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def
pyParamsDefaults: String
- Attributes
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lazy val
pyParamsDefinitions: String
- Attributes
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- Definition Classes
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def
pyParamsGetters: String
- Attributes
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- Definition Classes
- PythonWrappable
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def
pyParamsSetters: String
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def
pythonClass(): String
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def
rClass(): String
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def
rDocString: String
- Attributes
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def
rExtraBodyLines: String
- Attributes
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- Definition Classes
- RWrappable
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def
rExtraInitLines: String
- Attributes
- protected
- Definition Classes
- RWrappable
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lazy val
rFuncName: String
- Attributes
- protected
- Definition Classes
- RWrappable
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lazy val
rInternalWrapper: Boolean
- Attributes
- protected
- Definition Classes
- RWrappable
-
def
rParamArg[T](p: Param[T]): String
- Attributes
- protected
- Definition Classes
- RWrappable
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def
rParamsArgs: String
- Attributes
- protected
- Definition Classes
- RWrappable
-
def
rSetterLines: String
- Attributes
- protected
- Definition Classes
- RWrappable
-
def
save(path: String): Unit
- Definition Classes
- MLWritable
- Annotations
- @Since( "1.6.0" ) @throws( ... )
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final
def
set(paramPair: ParamPair[_]): ClassBalancerModel.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set(param: String, value: Any): ClassBalancerModel.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set[T](param: Param[T], value: T): ClassBalancerModel.this.type
- Definition Classes
- Params
- def setBroadcastJoin(v: Boolean): ClassBalancerModel.this.type
-
final
def
setDefault(paramPairs: ParamPair[_]*): ClassBalancerModel.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
setDefault[T](param: Param[T], value: T): ClassBalancerModel.this.type
- Attributes
- protected[org.apache.spark.ml]
- Definition Classes
- Params
-
def
setInputCol(value: String): ClassBalancerModel.this.type
- Definition Classes
- HasInputCol
-
def
setOutputCol(value: String): ClassBalancerModel.this.type
- Definition Classes
- HasOutputCol
-
def
setParent(parent: Estimator[ClassBalancerModel]): ClassBalancerModel
- Definition Classes
- Model
- def setWeights(v: DataFrame): ClassBalancerModel.this.type
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
-
val
thisStage: Params
- Attributes
- protected
- Definition Classes
- BaseWrappable
-
def
toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
-
def
transform(dataset: Dataset[_]): DataFrame
- Definition Classes
- ClassBalancerModel → Transformer
-
def
transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" )
-
def
transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" ) @varargs()
-
def
transformSchema(schema: StructType): StructType
- Definition Classes
- ClassBalancerModel → PipelineStage
-
def
transformSchema(schema: StructType, logging: Boolean): StructType
- Attributes
- protected
- Definition Classes
- PipelineStage
- Annotations
- @DeveloperApi()
-
val
uid: String
- Definition Classes
- ClassBalancerModel → SynapseMLLogging → Identifiable
-
final
def
wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
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- @throws( ... )
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final
def
wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
- val weights: DataFrameParam
-
def
write: MLWriter
- Definition Classes
- ComplexParamsWritable → MLWritable