c
com.microsoft.azure.synapse.ml.train
ComputeModelStatistics
Companion object ComputeModelStatistics
class ComputeModelStatistics extends Transformer with ComputeModelStatisticsParams with BasicLogging
Evaluates the given scored dataset.
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- ComputeModelStatistics
- BasicLogging
- ComputeModelStatisticsParams
- HasEvaluationMetric
- HasScoredLabelsCol
- HasScoresCol
- HasLabelCol
- DefaultParamsWritable
- MLWritable
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lazy val
classNameHelper: String
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def
clear(param: Param[_]): ComputeModelStatistics.this.type
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def
companionModelClassName: String
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def
copy(extra: ParamMap): Transformer
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- ComputeModelStatistics → 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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def
defaultCopy[T <: Params](extra: ParamMap): T
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def
eq(arg0: AnyRef): Boolean
- Definition Classes
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def
equals(arg0: Any): Boolean
- Definition Classes
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val
evaluationMetric: Param[String]
- Definition Classes
- HasEvaluationMetric
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def
explainParam(param: Param[_]): String
- Definition Classes
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explainParams(): String
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def
extractParamMap(): ParamMap
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extractParamMap(extra: ParamMap): ParamMap
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finalize(): Unit
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def
getDefault[T](param: Param[T]): Option[T]
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def
getEvaluationMetric: String
- Definition Classes
- HasEvaluationMetric
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def
getLabelCol: String
- Definition Classes
- HasLabelCol
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final
def
getOrDefault[T](param: Param[T]): T
- Definition Classes
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def
getParam(paramName: String): Param[Any]
- Definition Classes
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def
getScoredLabelsCol: String
- Definition Classes
- HasScoredLabelsCol
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def
getScoresCol: String
- Definition Classes
- HasScoresCol
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final
def
hasDefault[T](param: Param[T]): Boolean
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hasParam(paramName: String): Boolean
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hashCode(): Int
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initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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initializeLogIfNecessary(isInterpreter: Boolean): Unit
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isTraceEnabled(): Boolean
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val
labelCol: Param[String]
The name of the label column
The name of the label column
- Definition Classes
- HasLabelCol
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log: Logger
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logName: String
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logPredict[T](f: ⇒ T): T
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makePyFile(conf: CodegenConfig): Unit
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lazy val
params: Array[Param[_]]
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pyClassDoc: String
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pyParamsDefaults: String
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pyParamsGetters: String
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rInternalWrapper: Boolean
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rSetterLines: String
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var
rocCurve: DataFrame
The ROC curve evaluated for a binary classifier.
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def
save(path: String): Unit
- Definition Classes
- MLWritable
- Annotations
- @Since( "1.6.0" ) @throws( ... )
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val
scoredLabelsCol: Param[String]
The name of the scored labels column
The name of the scored labels column
- Definition Classes
- HasScoredLabelsCol
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val
scoresCol: Param[String]
The name of the scores column
The name of the scores column
- Definition Classes
- HasScoresCol
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final
def
set(paramPair: ParamPair[_]): ComputeModelStatistics.this.type
- Attributes
- protected
- Definition Classes
- Params
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final
def
set(param: String, value: Any): ComputeModelStatistics.this.type
- Attributes
- protected
- Definition Classes
- Params
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final
def
set[T](param: Param[T], value: T): ComputeModelStatistics.this.type
- Definition Classes
- Params
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final
def
setDefault(paramPairs: ParamPair[_]*): ComputeModelStatistics.this.type
- Attributes
- protected
- Definition Classes
- Params
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final
def
setDefault[T](param: Param[T], value: T): ComputeModelStatistics.this.type
- Attributes
- protected
- Definition Classes
- Params
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def
setEvaluationMetric(value: String): ComputeModelStatistics.this.type
- Definition Classes
- HasEvaluationMetric
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def
setLabelCol(value: String): ComputeModelStatistics.this.type
- Definition Classes
- HasLabelCol
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def
setScoredLabelsCol(value: String): ComputeModelStatistics.this.type
- Definition Classes
- HasScoredLabelsCol
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def
setScoresCol(value: String): ComputeModelStatistics.this.type
- Definition Classes
- HasScoresCol
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final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
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def
toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
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def
transform(dataset: Dataset[_]): DataFrame
Calculates the metrics for the given dataset and model.
Calculates the metrics for the given dataset and model.
- dataset
the dataset to calculate the metrics for
- returns
DataFrame whose columns contain the calculated metrics
- Definition Classes
- ComputeModelStatistics → Transformer
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def
transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" )
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def
transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" ) @varargs()
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def
transformSchema(schema: StructType): StructType
- Definition Classes
- ComputeModelStatistics → PipelineStage
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def
transformSchema(schema: StructType, logging: Boolean): StructType
- Attributes
- protected
- Definition Classes
- PipelineStage
- Annotations
- @DeveloperApi()
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val
uid: String
- Definition Classes
- ComputeModelStatistics → BasicLogging → Identifiable
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val
ver: String
- Definition Classes
- BasicLogging
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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
- Definition Classes
- DefaultParamsWritable → MLWritable