org.apache.spark.ml.classification

Class ClassificationModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>>

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

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

org.apache.spark.ml.impl.estimator.PredictionModel<FeaturesType,M>

org.apache.spark.ml.classification.ClassificationModel<FeaturesType,M>

All Implemented Interfaces:

java.io.Serializable, Logging, ClassifierParams, Identifiable, PredictorParams, HasFeaturesCol, HasLabelCol, HasPredictionCol, HasRawPredictionCol, Params

Direct Known Subclasses:

ProbabilisticClassificationModel

public abstract class ClassificationModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>>
extends PredictionModel<FeaturesType,M>
implements ClassifierParams

:: AlphaComponent :: Model produced by a Classifier. Classes are indexed {0, 1, ..., numClasses - 1}.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
ClassificationModel()

Method Summary

Methods

Modifier and Type	Method and Description
abstract int	numClasses() Number of classes (values which the label can take).
M	setRawPredictionCol(String value)
DataFrame	transform(DataFrame dataset, ParamMap paramMap) Transforms dataset by reading from featuresCol, and appending new columns as specified by parameters: - predicted labels as predictionCol of type Double - raw predictions (confidences) as rawPredictionCol of type Vector.
static <FeaturesType> scala.Tuple2<Object,DataFrame>	transformColumnsImpl(DataFrame dataset, ClassificationModel<FeaturesType,?> model, ParamMap map) Added prediction column(s).

Methods inherited from class org.apache.spark.ml.impl.estimator.PredictionModel

setFeaturesCol, setPredictionCol, transformSchema

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

fittingParamMap, parent

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

transform, transform

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.ml.classification.ClassifierParams

validateAndTransformSchema

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

getLabelCol, labelCol

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

featuresCol, getFeaturesCol

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

getPredictionCol, predictionCol

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

addOutputColumn, checkInputColumn, explainParams, get, getParam, isSet, paramMap, params, set, set, validate, validate

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

uid

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

getRawPredictionCol, rawPredictionCol

Methods inherited from interface org.apache.spark.Logging

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

Constructor Detail

ClassificationModel

public ClassificationModel()

Method Detail

transformColumnsImpl

public static <FeaturesType> scala.Tuple2<Object,DataFrame> transformColumnsImpl(DataFrame dataset,
                                                                 ClassificationModel<FeaturesType,?> model,
                                                                 ParamMap map)

Added prediction column(s). This is separated from ClassificationModel.transform() since it is used by ProbabilisticClassificationModel.

Parameters:

dataset - Input dataset

map - Parameter map. This will NOT be merged with the embedded paramMap; the merge should already be done.

Returns:

(number of columns added, transformed dataset)

setRawPredictionCol

public M setRawPredictionCol(String value)

numClasses

public abstract int numClasses()

Number of classes (values which the label can take).

transform

public DataFrame transform(DataFrame dataset,
                  ParamMap paramMap)

Transforms dataset by reading from featuresCol, and appending new columns as specified by parameters: - predicted labels as predictionCol of type Double - raw predictions (confidences) as rawPredictionCol of type Vector.

Overrides:

transform in class PredictionModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>>

Parameters:

dataset - input dataset

paramMap - additional parameters, overwrite embedded params

Returns:

transformed dataset