public class TrainValidationSplitModel extends Model<TrainValidationSplitModel> implements TrainValidationSplitParams, MLWritable
param: uid Id. param: bestModel Estimator determined best model. param: validationMetrics Evaluated validation metrics.
Modifier and Type | Class and Description |
---|---|
static class |
TrainValidationSplitModel.TrainValidationSplitModelWriter
Writer for TrainValidationSplitModel.
|
Modifier and Type | Method and Description |
---|---|
Model<?> |
bestModel() |
TrainValidationSplitModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
Param<Estimator<?>> |
estimator()
param for the estimator to be validated
|
Param<ParamMap[]> |
estimatorParamMaps()
param for estimator param maps
|
Param<Evaluator> |
evaluator()
param for the evaluator used to select hyper-parameters that maximize the validated metric
|
boolean |
hasSubModels() |
static TrainValidationSplitModel |
load(String path) |
static MLReader<TrainValidationSplitModel> |
read() |
LongParam |
seed()
Param for random seed.
|
Model<?>[] |
subModels() |
String |
toString() |
DoubleParam |
trainRatio()
Param for ratio between train and validation data.
|
Dataset<Row> |
transform(Dataset<?> dataset)
Transforms the input dataset.
|
StructType |
transformSchema(StructType schema)
Check transform validity and derive the output schema from the input schema.
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
double[] |
validationMetrics() |
TrainValidationSplitModel.TrainValidationSplitModelWriter |
write()
Returns an
MLWriter instance for this ML instance. |
transform, transform, transform
params
getTrainRatio
getEstimator, getEstimatorParamMaps, getEvaluator, logTuningParams, transformSchemaImpl
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
save
$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize
public static MLReader<TrainValidationSplitModel> read()
public static TrainValidationSplitModel load(String path)
public DoubleParam trainRatio()
TrainValidationSplitParams
trainRatio
in interface TrainValidationSplitParams
public Param<Estimator<?>> estimator()
ValidatorParams
estimator
in interface ValidatorParams
public Param<ParamMap[]> estimatorParamMaps()
ValidatorParams
estimatorParamMaps
in interface ValidatorParams
public Param<Evaluator> evaluator()
ValidatorParams
evaluator
in interface ValidatorParams
public final LongParam seed()
HasSeed
public String uid()
Identifiable
uid
in interface Identifiable
public Model<?> bestModel()
public double[] validationMetrics()
public Model<?>[] subModels()
IllegalArgumentException
- if subModels are not available. To retrieve subModels,
make sure to set collectSubModels to true before fitting.public boolean hasSubModels()
public Dataset<Row> transform(Dataset<?> dataset)
Transformer
transform
in class Transformer
dataset
- (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
We check validity for interactions between parameters during transformSchema
and
raise an exception if any parameter value is invalid. Parameter value checks which
do not depend on other parameters are handled by Param.validate()
.
Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
transformSchema
in class PipelineStage
schema
- (undocumented)public TrainValidationSplitModel copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Model<TrainValidationSplitModel>
extra
- (undocumented)public TrainValidationSplitModel.TrainValidationSplitModelWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface MLWritable
public String toString()
toString
in interface Identifiable
toString
in class Object