CrossValidatorModel (Spark 2.2.2 JavaDoc)

Object
- org.apache.spark.ml.PipelineStage
- - org.apache.spark.ml.Transformer
  - - org.apache.spark.ml.Model<CrossValidatorModel>
    - - org.apache.spark.ml.tuning.CrossValidatorModel

All Implemented Interfaces:

java.io.Serializable, Logging, Params, Identifiable, MLWritable
```
public class CrossValidatorModel
extends Model<CrossValidatorModel>
implements MLWritable
```
CrossValidatorModel contains the model with the highest average cross-validation metric across folds and uses this model to transform input data. CrossValidatorModel also tracks the metrics for each param map evaluated.
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.

See Also:

Serialized Form

Method Summary

All Methods Static Methods Instance Methods Abstract Methods Concrete Methods
Modifier and Type	Method and Description
`double[]`	`avgMetrics()`
`Model<?>`	`bestModel()`
`static Params`	`clear(Param<?> param)`
`CrossValidatorModel`	`copy(ParamMap extra)` Creates a copy of this instance with the same UID and some extra params.
`static Param<Estimator<?>>`	`estimator()`
`Param<Estimator<?>>`	`estimator()` param for the estimator to be validated
`static Param<ParamMap[]>`	`estimatorParamMaps()`
`Param<ParamMap[]>`	`estimatorParamMaps()` param for estimator param maps
`static Param<Evaluator>`	`evaluator()`
`Param<Evaluator>`	`evaluator()` param for the evaluator used to select hyper-parameters that maximize the validated metric
`static String`	`explainParam(Param<?> param)`
`static String`	`explainParams()`
`static ParamMap`	`extractParamMap()`
`static ParamMap`	`extractParamMap(ParamMap extra)`
`static <T> scala.Option<T>`	`get(Param<T> param)`
`static <T> scala.Option<T>`	`getDefault(Param<T> param)`
`static Estimator<?>`	`getEstimator()`
`Estimator<?>`	`getEstimator()`
`static ParamMap[]`	`getEstimatorParamMaps()`
`ParamMap[]`	`getEstimatorParamMaps()`
`static Evaluator`	`getEvaluator()`
`Evaluator`	`getEvaluator()`
`static int`	`getNumFolds()`
`int`	`getNumFolds()`
`static <T> T`	`getOrDefault(Param<T> param)`
`static Param<Object>`	`getParam(String paramName)`
`static long`	`getSeed()`
`static <T> boolean`	`hasDefault(Param<T> param)`
`static boolean`	`hasParam(String paramName)`
`static boolean`	`hasParent()`
`static boolean`	`isDefined(Param<?> param)`
`static boolean`	`isSet(Param<?> param)`
`static CrossValidatorModel`	`load(String path)`
`void`	`logTuningParams(<any> instrumentation)` Instrumentation logging for tuning params including the inner estimator and evaluator info.
`static IntParam`	`numFolds()`
`IntParam`	`numFolds()` Param for number of folds for cross validation.
`static Param<?>[]`	`params()`
`static void`	`parent_$eq(Estimator<M> x$1)`
`static Estimator<M>`	`parent()`
`static MLReader<CrossValidatorModel>`	`read()`
`static void`	`save(String path)`
`static LongParam`	`seed()`
`static <T> Params`	`set(Param<T> param, T value)`
`static M`	`setParent(Estimator<M> parent)`
`static String`	`toString()`
`Dataset<Row>`	`transform(Dataset<?> dataset)` Transforms the input dataset.
`StructType`	`transformSchema(StructType schema)` :: DeveloperApi ::
`StructType`	`transformSchemaImpl(StructType schema)`
`String`	`uid()` An immutable unique ID for the object and its derivatives.
`MLWriter`	`write()` Returns an `MLWriter` instance for this ML instance.

Methods inherited from class org.apache.spark.ml.Model
hasParent, parent, setParent

Methods inherited from class org.apache.spark.ml.Transformer
transform, transform, transform

Methods inherited from class Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.ml.param.Params
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.util.Identifiable
toString

Methods inherited from interface org.apache.spark.ml.util.MLWritable
save

Methods inherited from interface org.apache.spark.internal.Logging
initializeLogging, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

- Method Detail
  - read
```
public static MLReader<CrossValidatorModel> read()
```
  - load
```
public static CrossValidatorModel load(String path)
```
  - toString
```
public static String toString()
```
  - params
```
public static Param<?>[] params()
```
  - explainParam
```
public static String explainParam(Param<?> param)
```
  - explainParams
```
public static String explainParams()
```
  - isSet
```
public static final boolean isSet(Param<?> param)
```
  - isDefined
```
public static final boolean isDefined(Param<?> param)
```
  - hasParam
```
public static boolean hasParam(String paramName)
```
  - getParam
```
public static Param<Object> getParam(String paramName)
```
  - set
```
public static final <T> Params set(Param<T> param,
                                   T value)
```
  - get
```
public static final <T> scala.Option<T> get(Param<T> param)
```
  - clear
```
public static final Params clear(Param<?> param)
```
  - getOrDefault
```
public static final <T> T getOrDefault(Param<T> param)
```
  - getDefault
```
public static final <T> scala.Option<T> getDefault(Param<T> param)
```
  - hasDefault
```
public static final <T> boolean hasDefault(Param<T> param)
```
  - extractParamMap
```
public static final ParamMap extractParamMap(ParamMap extra)
```
  - extractParamMap
```
public static final ParamMap extractParamMap()
```
  - parent
```
public static Estimator<M> parent()
```
  - parent_$eq
```
public static void parent_$eq(Estimator<M> x$1)
```
  - setParent
```
public static M setParent(Estimator<M> parent)
```
  - hasParent
```
public static boolean hasParent()
```
  - seed
```
public static final LongParam seed()
```
  - getSeed
```
public static final long getSeed()
```
  - estimator
```
public static Param<Estimator<?>> estimator()
```
  - getEstimator
```
public static Estimator<?> getEstimator()
```
  - estimatorParamMaps
```
public static Param<ParamMap[]> estimatorParamMaps()
```
  - getEstimatorParamMaps
```
public static ParamMap[] getEstimatorParamMaps()
```
  - evaluator
```
public static Param<Evaluator> evaluator()
```
  - getEvaluator
```
public static Evaluator getEvaluator()
```
  - numFolds
```
public static IntParam numFolds()
```
  - getNumFolds
```
public static int getNumFolds()
```
  - save
```
public static void save(String path)
                 throws java.io.IOException
```
    Throws:
    
    java.io.IOException
  - uid
```
public String uid()
```
    Description copied from interface: Identifiable
    
    An immutable unique ID for the object and its derivatives.
    
    Specified by:
    
    uid in interface Identifiable
    
    Returns:
    
    (undocumented)
  - bestModel
```
public Model<?> bestModel()
```
  - avgMetrics
```
public double[] avgMetrics()
```
  - transform
```
public Dataset<Row> transform(Dataset<?> dataset)
```
    Description copied from class: Transformer
    
    Transforms the input dataset.
    
    Specified by:
    
    transform in class Transformer
    
    Parameters:
    
    dataset - (undocumented)
    
    Returns:
    
    (undocumented)
  - transformSchema
```
public StructType transformSchema(StructType schema)
```
    Description copied from class: PipelineStage
    
    :: DeveloperApi ::
    Check 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.
    
    Specified by:
    
    transformSchema in class PipelineStage
    
    Parameters:
    
    schema - (undocumented)
    
    Returns:
    
    (undocumented)
  - copy
```
public CrossValidatorModel copy(ParamMap extra)
```
    Description copied from interface: Params
    
    Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy().
    
    Specified by:
    
    copy in interface Params
    
    Specified by:
    
    copy in class Model<CrossValidatorModel>
    
    Parameters:
    
    extra - (undocumented)
    
    Returns:
    
    (undocumented)
  - write
```
public MLWriter write()
```
    Description copied from interface: MLWritable
    
    Returns an MLWriter instance for this ML instance.
    
    Specified by:
    
    write in interface MLWritable
    
    Returns:
    
    (undocumented)
  - numFolds
```
public IntParam numFolds()
```
    Param for number of folds for cross validation. Must be >= 2. Default: 3
    
    Returns:
    
    (undocumented)
  - getNumFolds
```
public int getNumFolds()
```
  - estimator
```
public Param<Estimator<?>> estimator()
```
    param for the estimator to be validated
    
    Returns:
    
    (undocumented)
  - getEstimator
```
public Estimator<?> getEstimator()
```
  - estimatorParamMaps
```
public Param<ParamMap[]> estimatorParamMaps()
```
    param for estimator param maps
    
    Returns:
    
    (undocumented)
  - getEstimatorParamMaps
```
public ParamMap[] getEstimatorParamMaps()
```
  - evaluator
```
public Param<Evaluator> evaluator()
```
    param for the evaluator used to select hyper-parameters that maximize the validated metric
    
    Returns:
    
    (undocumented)
  - getEvaluator
```
public Evaluator getEvaluator()
```
  - transformSchemaImpl
```
public StructType transformSchemaImpl(StructType schema)
```
  - logTuningParams
```
public void logTuningParams(<any> instrumentation)
```
    Instrumentation logging for tuning params including the inner estimator and evaluator info.
    
    Parameters:
    
    instrumentation - (undocumented)

Class CrossValidatorModel

Method Summary

Methods inherited from class org.apache.spark.ml.Model

Methods inherited from class org.apache.spark.ml.Transformer

Methods inherited from class Object

Methods inherited from interface org.apache.spark.ml.param.Params

Methods inherited from interface org.apache.spark.ml.util.Identifiable

Methods inherited from interface org.apache.spark.ml.util.MLWritable

Methods inherited from interface org.apache.spark.internal.Logging

Method Detail

read

load

toString

params

explainParam

explainParams

isSet

isDefined

hasParam

getParam

set

get

clear

getOrDefault

getDefault

hasDefault

extractParamMap

extractParamMap

parent

parent_$eq

setParent

hasParent

seed

getSeed

estimator

getEstimator

estimatorParamMaps

getEstimatorParamMaps

evaluator

getEvaluator

numFolds

getNumFolds

save

uid

bestModel

avgMetrics

transform

transformSchema

copy

write

numFolds

getNumFolds

estimator

getEstimator

estimatorParamMaps

getEstimatorParamMaps

evaluator

getEvaluator

transformSchemaImpl

logTuningParams