c
com.microsoft.azure.synapse.ml.train
TrainedClassifierModel
Companion object TrainedClassifierModel
class TrainedClassifierModel extends AutoTrainedModel[TrainedClassifierModel] with Wrappable with SynapseMLLogging
Model produced by TrainClassifier.
Linear Supertypes
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Inherited
- TrainedClassifierModel
- SynapseMLLogging
- Wrappable
- RWrappable
- PythonWrappable
- BaseWrappable
- AutoTrainedModel
- HasFeaturesCol
- HasLabelCol
- ComplexParamsWritable
- MLWritable
- Model
- Transformer
- PipelineStage
- Logging
- Params
- Serializable
- Serializable
- Identifiable
- AnyRef
- Any
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Value Members
-
final
def
clear(param: Param[_]): TrainedClassifierModel.this.type
- Definition Classes
- Params
-
def
copy(extra: ParamMap): TrainedClassifierModel
- Definition Classes
- TrainedClassifierModel → Model → Transformer → PipelineStage → Params
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def
explainParam(param: Param[_]): String
- Definition Classes
- Params
-
def
explainParams(): String
- Definition Classes
- Params
-
final
def
extractParamMap(): ParamMap
- Definition Classes
- Params
-
final
def
extractParamMap(extra: ParamMap): ParamMap
- Definition Classes
- Params
-
val
featuresCol: Param[String]
The name of the features column
The name of the features column
- Definition Classes
- HasFeaturesCol
-
final
def
get[T](param: Param[T]): Option[T]
- Definition Classes
- Params
-
final
def
getDefault[T](param: Param[T]): Option[T]
- Definition Classes
- Params
-
def
getFeaturesCol: String
- Definition Classes
- HasFeaturesCol
-
def
getLabelCol: String
- Definition Classes
- HasLabelCol
-
def
getLastStage: Transformer
Retrieve the underlying model.
- def getLevels: Array[Any]
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def
getModel: PipelineModel
- Definition Classes
- AutoTrainedModel
-
final
def
getOrDefault[T](param: Param[T]): T
- Definition Classes
- Params
-
def
getParam(paramName: String): Param[Any]
- Definition Classes
- Params
-
def
getParamInfo(p: Param[_]): ParamInfo[_]
- Definition Classes
- BaseWrappable
-
def
getParamMap: ParamMap
Retrieve the param map from the underlying model.
Retrieve the param map from the underlying model.
- returns
The param map from the underlying model.
- Definition Classes
- AutoTrainedModel
-
final
def
hasDefault[T](param: Param[T]): Boolean
- Definition Classes
- Params
-
def
hasParam(paramName: String): Boolean
- Definition Classes
- Params
-
def
hasParent: Boolean
- Definition Classes
- Model
- def hasScoreColumns(model: Transformer): Boolean
-
final
def
isDefined(param: Param[_]): Boolean
- Definition Classes
- Params
-
final
def
isSet(param: Param[_]): Boolean
- Definition Classes
- Params
-
val
labelCol: Param[String]
The name of the label column
The name of the label column
- Definition Classes
- HasLabelCol
- val levels: UntypedArrayParam
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def
logClass(featureName: String): Unit
- Definition Classes
- SynapseMLLogging
-
def
logFit[T](f: ⇒ T, columns: Int): T
- Definition Classes
- SynapseMLLogging
-
def
logTransform[T](f: ⇒ T, columns: Int): T
- Definition Classes
- SynapseMLLogging
-
def
logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
- Definition Classes
- SynapseMLLogging
-
def
makePyFile(conf: CodegenConfig): Unit
- Definition Classes
- PythonWrappable
-
def
makeRFile(conf: CodegenConfig): Unit
- Definition Classes
- RWrappable
-
val
model: TransformerParam
- Definition Classes
- AutoTrainedModel
-
lazy val
params: Array[Param[_]]
- Definition Classes
- Params
-
var
parent: Estimator[TrainedClassifierModel]
- Definition Classes
- Model
-
def
pyAdditionalMethods: String
- Definition Classes
- PythonWrappable
-
def
pyInitFunc(): String
- Definition Classes
- PythonWrappable
-
def
save(path: String): Unit
- Definition Classes
- MLWritable
- Annotations
- @Since( "1.6.0" ) @throws( ... )
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final
def
set[T](param: Param[T], value: T): TrainedClassifierModel.this.type
- Definition Classes
- Params
-
def
setFeaturesCol(value: String): TrainedClassifierModel.this.type
- Definition Classes
- HasFeaturesCol
-
def
setLabelCol(value: String): TrainedClassifierModel.this.type
- Definition Classes
- HasLabelCol
- def setLevels(v: ArrayList[Any]): TrainedClassifierModel.this.type
- def setLevels(v: Array[_]): TrainedClassifierModel.this.type
-
def
setModel(v: PipelineModel): TrainedClassifierModel.this.type
- Definition Classes
- AutoTrainedModel
-
def
setParent(parent: Estimator[TrainedClassifierModel]): TrainedClassifierModel
- Definition Classes
- Model
-
def
toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
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def
transform(dataset: Dataset[_]): DataFrame
- Definition Classes
- TrainedClassifierModel → Transformer
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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
- TrainedClassifierModel → PipelineStage
- Annotations
- @DeveloperApi()
-
val
uid: String
- Definition Classes
- TrainedClassifierModel → SynapseMLLogging → Identifiable
-
def
write: MLWriter
- Definition Classes
- ComplexParamsWritable → MLWritable