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,- TrainValidationSplitParams,- ValidatorParams,- Identifiable,- MLWritable
public class TrainValidationSplitModel
extends Model<TrainValidationSplitModel>
implements TrainValidationSplitParams, MLWritable
Model from train validation split.
 
param: uid Id. param: bestModel Estimator determined best model. param: validationMetrics Evaluated validation metrics.
- See Also:
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Nested Class SummaryNested ClassesModifier and TypeClassDescriptionstatic final classWriter for TrainValidationSplitModel.Nested classes/interfaces inherited from interface org.apache.spark.internal.Loggingorg.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter
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Method SummaryModifier and TypeMethodDescriptionModel<?>Creates a copy of this instance with the same UID and some extra params.param for the estimator to be validatedparam for estimator param mapsparam for the evaluator used to select hyper-parameters that maximize the validated metricbooleanstatic TrainValidationSplitModelstatic MLReader<TrainValidationSplitModel>read()final LongParamseed()Param for random seed.Model<?>[]toString()Param for ratio between train and validation data.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.Transformertransform, transform, transformMethods inherited from class org.apache.spark.ml.PipelineStageparamsMethods inherited from class java.lang.Objectequals, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface org.apache.spark.internal.LogginginitializeForcefully, 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.MLWritablesaveMethods inherited from interface org.apache.spark.ml.param.Paramsclear, 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.TrainValidationSplitParamsgetTrainRatioMethods inherited from interface org.apache.spark.ml.tuning.ValidatorParamsgetEstimator, getEstimatorParamMaps, getEvaluator, logTuningParams, transformSchemaImpl
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Method Details- 
read
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load
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trainRatioDescription copied from interface:TrainValidationSplitParamsParam for ratio between train and validation data. Must be between 0 and 1. Default: 0.75- Specified by:
- trainRatioin interface- TrainValidationSplitParams
- Returns:
- (undocumented)
 
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estimatorDescription copied from interface:ValidatorParamsparam for the estimator to be validated- Specified by:
- estimatorin interface- ValidatorParams
- Returns:
- (undocumented)
 
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estimatorParamMapsDescription copied from interface:ValidatorParamsparam for estimator param maps- Specified by:
- estimatorParamMapsin interface- ValidatorParams
- Returns:
- (undocumented)
 
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evaluatorDescription copied from interface:ValidatorParamsparam for the evaluator used to select hyper-parameters that maximize the validated metric- Specified by:
- evaluatorin interface- ValidatorParams
- Returns:
- (undocumented)
 
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seedDescription copied from interface:HasSeedParam for random seed.
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uidDescription copied from interface:IdentifiableAn immutable unique ID for the object and its derivatives.- Specified by:
- uidin interface- Identifiable
- Returns:
- (undocumented)
 
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bestModel
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validationMetricspublic double[] validationMetrics()
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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.
 
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hasSubModelspublic boolean hasSubModels()
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transformDescription copied from class:TransformerTransforms the input dataset.- Specified by:
- transformin class- Transformer
- Parameters:
- dataset- (undocumented)
- Returns:
- (undocumented)
 
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transformSchemaDescription 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 class- PipelineStage
- Parameters:
- schema- (undocumented)
- Returns:
- (undocumented)
 
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copyDescription 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 interface- Params
- Specified by:
- copyin class- Model<TrainValidationSplitModel>
- Parameters:
- extra- (undocumented)
- Returns:
- (undocumented)
 
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writeDescription copied from interface:MLWritableReturns anMLWriterinstance for this ML instance.- Specified by:
- writein interface- MLWritable
- Returns:
- (undocumented)
 
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toString- Specified by:
- toStringin interface- Identifiable
- Overrides:
- toStringin class- Object
 
 
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