public class CrossValidatorModel extends Model<CrossValidatorModel> implements CrossValidatorParams, MLWritable
param: bestModel The best model selected from k-fold cross validation.
param: avgMetrics Average cross-validation metrics for each paramMap in
CrossValidator.estimatorParamMaps, in the corresponding order.
| Modifier and Type | Class and Description |
|---|---|
static class |
CrossValidatorModel.CrossValidatorModelWriter
Writer for CrossValidatorModel.
|
| Modifier and Type | Method and Description |
|---|---|
double[] |
avgMetrics() |
Model<?> |
bestModel() |
CrossValidatorModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
boolean |
hasSubModels() |
static CrossValidatorModel |
load(String path) |
static MLReader<CrossValidatorModel> |
read() |
Model<?>[][] |
subModels() |
Dataset<Row> |
transform(Dataset<?> dataset)
Transforms the input dataset.
|
StructType |
transformSchema(StructType schema)
:: DeveloperApi ::
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
CrossValidatorModel.CrossValidatorModelWriter |
write()
Returns an
MLWriter instance for this ML instance. |
transform, transform, transformequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitgetNumFolds, numFoldsestimator, estimatorParamMaps, evaluator, getEstimator, getEstimatorParamMaps, getEvaluator, logTuningParams, transformSchemaImplclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoStringsaveinitializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarningpublic static MLReader<CrossValidatorModel> read()
public static CrossValidatorModel load(String path)
public String uid()
Identifiableuid in interface Identifiablepublic Model<?> bestModel()
public double[] avgMetrics()
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)
Transformertransform in class Transformerdataset - (undocumented)public StructType transformSchema(StructType schema)
PipelineStageCheck transform validity and derive the output schema from the input schema.
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 PipelineStageschema - (undocumented)public CrossValidatorModel copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Model<CrossValidatorModel>extra - (undocumented)public CrossValidatorModel.CrossValidatorModelWriter write()
MLWritableMLWriter instance for this ML instance.write in interface MLWritable