org.apache.spark.ml.classification

Class OneVsRestModel

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

org.apache.spark.ml.Model<OneVsRestModel>

org.apache.spark.ml.classification.OneVsRestModel

All Implemented Interfaces:

java.io.Serializable, Logging, Params, Identifiable, MLWritable

public final class OneVsRestModel
extends Model<OneVsRestModel>
implements MLWritable

Model produced by OneVsRest. This stores the models resulting from training k binary classifiers: one for each class. Each example is scored against all k models, and the model with the highest score is picked to label the example.

param: labelMetadata Metadata of label column if it exists, or Nominal attribute representing the number of classes in training dataset otherwise. param: models The binary classification models for the reduction. The i-th model is produced by testing the i-th class (taking label 1) vs the rest (taking label 0).

See Also:

Serialized Form

Method Summary

Modifier and Type	Method and Description
static Param<Classifier<?,? extends Classifier<Object,Classifier,ClassificationModel>,? extends ClassificationModel<Object,ClassificationModel>>>	classifier()
Param<Classifier<?,? extends Classifier<Object,Classifier,ClassificationModel>,? extends ClassificationModel<Object,ClassificationModel>>>	classifier() param for the base binary classifier that we reduce multiclass classification into.
static Params	clear(Param<?> param)
OneVsRestModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
static String	explainParam(Param<?> param)
static String	explainParams()
static ParamMap	extractParamMap()
static ParamMap	extractParamMap(ParamMap extra)
static Param<String>	featuresCol()
static <T> scala.Option<T>	get(Param<T> param)
static Classifier<?,? extends Classifier<Object,Classifier,ClassificationModel>,? extends ClassificationModel<Object,ClassificationModel>>	getClassifier()
Classifier<?,? extends Classifier<Object,Classifier,ClassificationModel>,? extends ClassificationModel<Object,ClassificationModel>>	getClassifier()
static <T> scala.Option<T>	getDefault(Param<T> param)
static String	getFeaturesCol()
static String	getLabelCol()
static <T> T	getOrDefault(Param<T> param)
static Param<Object>	getParam(String paramName)
static String	getPredictionCol()
static String	getRawPredictionCol()
static String	getWeightCol()
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 Param<String>	labelCol()
static OneVsRestModel	load(String path)
ClassificationModel[]	models()
int	numClasses()
int	numFeatures()
static Param<?>[]	params()
static void	parent_$eq(Estimator<M> x$1)
static Estimator<M>	parent()
static Param<String>	predictionCol()
static Param<String>	rawPredictionCol()
static MLReader<OneVsRestModel>	read()
static void	save(String path)
static <T> Params	set(Param<T> param, T value)
OneVsRestModel	setFeaturesCol(String value)
static M	setParent(Estimator<M> parent)
OneVsRestModel	setPredictionCol(String value)
OneVsRestModel	setRawPredictionCol(String value)
static String	toString()
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.
StructType	validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
static Param<String>	weightCol()
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.shared.HasRawPredictionCol

getRawPredictionCol, rawPredictionCol

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.param.shared.HasWeightCol

getWeightCol, weightCol

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

save

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

initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Method Detail

read

public static MLReader<OneVsRestModel> read()

load

public static OneVsRestModel 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()

labelCol

public static final Param<String> labelCol()

getLabelCol

public static final String getLabelCol()

featuresCol

public static final Param<String> featuresCol()

getFeaturesCol

public static final String getFeaturesCol()

predictionCol

public static final Param<String> predictionCol()

getPredictionCol

public static final String getPredictionCol()

rawPredictionCol

public static final Param<String> rawPredictionCol()

getRawPredictionCol

public static final String getRawPredictionCol()

weightCol

public static final Param<String> weightCol()

getWeightCol

public static final String getWeightCol()

classifier

public static Param<Classifier<?,? extends Classifier<Object,Classifier,ClassificationModel>,? extends ClassificationModel<Object,ClassificationModel>>> classifier()

getClassifier

public static Classifier<?,? extends Classifier<Object,Classifier,ClassificationModel>,? extends ClassificationModel<Object,ClassificationModel>> getClassifier()

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)

models

public ClassificationModel[] models()

numClasses

public int numClasses()

numFeatures

public int numFeatures()

setFeaturesCol

public OneVsRestModel setFeaturesCol(String value)

setPredictionCol

public OneVsRestModel setPredictionCol(String value)

setRawPredictionCol

public OneVsRestModel setRawPredictionCol(String value)

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)

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)

copy

public OneVsRestModel 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<OneVsRestModel>

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)

classifier

public Param<Classifier<?,? extends Classifier<Object,Classifier,ClassificationModel>,? extends ClassificationModel<Object,ClassificationModel>>> classifier()

param for the base binary classifier that we reduce multiclass classification into. The base classifier input and output columns are ignored in favor of the ones specified in OneVsRest.

Returns:

(undocumented)

getClassifier

public Classifier<?,? extends Classifier<Object,Classifier,ClassificationModel>,? extends ClassificationModel<Object,ClassificationModel>> getClassifier()

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema,
                                             boolean fitting,
                                             DataType featuresDataType)