Package org.apache.spark.ml.tuning
Class TrainValidationSplitModel
Object
org.apache.spark.ml.PipelineStage
org.apache.spark.ml.Transformer
org.apache.spark.ml.Model<TrainValidationSplitModel>
org.apache.spark.ml.tuning.TrainValidationSplitModel
- All Implemented Interfaces:
Serializable,org.apache.spark.internal.Logging,Params,HasSeed,org.apache.spark.ml.tuning.TrainValidationSplitParams,org.apache.spark.ml.tuning.ValidatorParams,Identifiable,MLWritable
public class TrainValidationSplitModel
extends Model<TrainValidationSplitModel>
implements org.apache.spark.ml.tuning.TrainValidationSplitParams, MLWritable
Model from train validation split.
param: uid Id. param: bestModel Estimator determined best model. param: validationMetrics Evaluated validation metrics.
- See Also:
-
Nested Class Summary
Nested ClassesModifier and TypeClassDescriptionstatic final classWriter for TrainValidationSplitModel.Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging
org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter -
Method Summary
Modifier and TypeMethodDescriptionModel<?>Creates a copy of this instance with the same UID and some extra params.booleanstatic TrainValidationSplitModelstatic MLReader<TrainValidationSplitModel>read()final LongParamseed()Param for random seed.Model<?>[]toString()Transforms the input dataset.transformSchema(StructType schema) Check transform validity and derive the output schema from the input schema.uid()An immutable unique ID for the object and its derivatives.double[]write()Returns anMLWriterinstance for this ML instance.Methods inherited from class org.apache.spark.ml.Transformer
transform, transform, transformMethods inherited from class org.apache.spark.ml.PipelineStage
paramsMethods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface org.apache.spark.internal.Logging
initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logBasedOnLevel, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, MDC, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContextMethods inherited from interface org.apache.spark.ml.util.MLWritable
saveMethods inherited from interface org.apache.spark.ml.param.Params
clear, copyValues, defaultCopy, defaultParamMap, estimateMatadataSize, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwnMethods inherited from interface org.apache.spark.ml.tuning.TrainValidationSplitParams
getTrainRatio, org$apache$spark$ml$tuning$TrainValidationSplitParams$_setter_$trainRatio_$eqMethods inherited from interface org.apache.spark.ml.tuning.ValidatorParams
getEstimator, getEstimatorParamMaps, getEvaluator, logTuningParams, org$apache$spark$ml$tuning$ValidatorParams$_setter_$estimator_$eq, org$apache$spark$ml$tuning$ValidatorParams$_setter_$estimatorParamMaps_$eq, org$apache$spark$ml$tuning$ValidatorParams$_setter_$evaluator_$eq, transformSchemaImpl
-
Method Details
-
read
-
load
-
trainRatio
- Specified by:
trainRatioin interfaceorg.apache.spark.ml.tuning.TrainValidationSplitParams
-
estimator
- Specified by:
estimatorin interfaceorg.apache.spark.ml.tuning.ValidatorParams
-
estimatorParamMaps
- Specified by:
estimatorParamMapsin interfaceorg.apache.spark.ml.tuning.ValidatorParams
-
evaluator
- Specified by:
evaluatorin interfaceorg.apache.spark.ml.tuning.ValidatorParams
-
seed
Description copied from interface:HasSeedParam for random seed. -
uid
Description copied from interface:IdentifiableAn immutable unique ID for the object and its derivatives.- Specified by:
uidin interfaceIdentifiable- Returns:
- (undocumented)
-
bestModel
-
validationMetrics
public double[] validationMetrics() -
subModels
- Returns:
- submodels represented in array. The index of array corresponds to the ordering of estimatorParamMaps
- Throws:
IllegalArgumentException- if subModels are not available. To retrieve subModels, make sure to set collectSubModels to true before fitting.
-
hasSubModels
public boolean hasSubModels() -
transform
Description copied from class:TransformerTransforms the input dataset.- Specified by:
transformin classTransformer- Parameters:
dataset- (undocumented)- Returns:
- (undocumented)
-
transformSchema
Description copied from class:PipelineStageCheck transform validity and derive the output schema from the input schema.We check validity for interactions between parameters during
transformSchemaand raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled byParam.validate().Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
- Specified by:
transformSchemain classPipelineStage- Parameters:
schema- (undocumented)- Returns:
- (undocumented)
-
copy
Description copied from interface:ParamsCreates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. SeedefaultCopy().- Specified by:
copyin interfaceParams- Specified by:
copyin classModel<TrainValidationSplitModel>- Parameters:
extra- (undocumented)- Returns:
- (undocumented)
-
write
Description copied from interface:MLWritableReturns anMLWriterinstance for this ML instance.- Specified by:
writein interfaceMLWritable- Returns:
- (undocumented)
-
toString
- Specified by:
toStringin interfaceIdentifiable- Overrides:
toStringin classObject
-