class FastVectorAssembler extends Transformer with HasInputCols with HasOutputCol with DefaultParamsWritable
A fast vector assembler. The columns given must be ordered such that categorical columns come first (otherwise spark learners will give categorical attributes to the wrong index). Does not keep spurious numeric data which can significantly slow down computations when there are millions of columns.
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def
clear(param: Param[_]): FastVectorAssembler.this.type
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clone(): AnyRef
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def
copy(extra: ParamMap): FastVectorAssembler
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copyValues[T <: Params](to: T, extra: ParamMap): T
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defaultCopy[T <: Params](extra: ParamMap): T
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getDefault[T](param: Param[T]): Option[T]
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def
getInputCols: Array[String]
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def
getOrDefault[T](param: Param[T]): T
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def
getOutputCol: String
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val
inputCols: StringArrayParam
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log: Logger
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logName: String
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logWarning(msg: ⇒ String, throwable: Throwable): Unit
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logWarning(msg: ⇒ String): Unit
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def
notifyAll(): Unit
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final
val
outputCol: Param[String]
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lazy val
params: Array[Param[_]]
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def
save(path: String): Unit
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- @Since( "1.6.0" ) @throws( ... )
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final
def
set(paramPair: ParamPair[_]): FastVectorAssembler.this.type
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final
def
set(param: String, value: Any): FastVectorAssembler.this.type
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final
def
set[T](param: Param[T], value: T): FastVectorAssembler.this.type
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final
def
setDefault(paramPairs: ParamPair[_]*): FastVectorAssembler.this.type
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final
def
setDefault[T](param: Param[T], value: T): FastVectorAssembler.this.type
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- Params
- def setInputCols(value: Array[String]): FastVectorAssembler.this.type
- def setOutputCol(value: String): FastVectorAssembler.this.type
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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def
transform(dataset: Dataset[_]): DataFrame
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- FastVectorAssembler → Transformer
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def
transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
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- Transformer
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- @Since( "2.0.0" )
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def
transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
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- Transformer
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- @Since( "2.0.0" ) @varargs()
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def
transformSchema(schema: StructType): StructType
- Definition Classes
- FastVectorAssembler → PipelineStage
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def
transformSchema(schema: StructType, logging: Boolean): StructType
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val
uid: String
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- FastVectorAssembler → Identifiable
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final
def
wait(): Unit
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def
wait(arg0: Long, arg1: Int): Unit
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def
wait(arg0: Long): Unit
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def
write: MLWriter
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