package ml
Linear Supertypes
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Type Members
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abstract
class
BaseRegressor[F, R <: Regressor[F, R, M], M <: RegressionModel[F, M]] extends Regressor[F, R, M]
Temporary hack to expose private Regressor class in SparkML as a developer API
- trait ComplexParamsReadable[T] extends MLReadable[T]
- trait ComplexParamsWritable extends MLWritable
- class DFSerializer extends Serializer[DataFrame]
- class ObjectSerializer[O] extends Serializer[O]
- class PipelineArraySerializer extends Serializer[Array[PipelineStage]]
- class PipelineSerializer extends Serializer[PipelineStage]
-
abstract
class
Ranker[FeaturesType, Learner <: Ranker[FeaturesType, Learner, M], M <: RankerModel[FeaturesType, M]] extends Predictor[FeaturesType, Learner, M] with PredictorParams with HasGroupCol
Ranker base class
Ranker base class
- FeaturesType
Type of input features. E.g., org.apache.spark.mllib.linalg.Vector
- Learner
Concrete Estimator type
- M
Concrete Model type
-
abstract
class
RankerModel[FeaturesType, M <: RankerModel[FeaturesType, M]] extends PredictionModel[FeaturesType, M] with PredictorParams
Model produced by a
Ranker.Model produced by a
Ranker.- FeaturesType
Type of input features. E.g., org.apache.spark.mllib.linalg.Vector
- M
Concrete Model type.
- abstract class Serializer[O] extends AnyRef
Value Members
- object ImageInjections
- object NamespaceInjections
- object ParamInjections
- object Serializer