org.apache.spark.ml.classification

Class MultilayerPerceptronClassificationModel

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

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

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

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

org.apache.spark.ml.classification.ProbabilisticClassificationModel<Vector,MultilayerPerceptronClassificationModel>

org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel

All Implemented Interfaces:

java.io.Serializable, Logging, ClassifierParams, ProbabilisticClassifierParams, Params, HasFeaturesCol, HasLabelCol, HasPredictionCol, HasProbabilityCol, HasRawPredictionCol, HasThresholds, PredictorParams, Identifiable, MLWritable

public class MultilayerPerceptronClassificationModel
extends ProbabilisticClassificationModel<Vector,MultilayerPerceptronClassificationModel>
implements scala.Serializable, MLWritable

Classification model based on the Multilayer Perceptron. Each layer has sigmoid activation function, output layer has softmax.

param: uid uid param: layers array of layer sizes including input and output layers param: weights the weights of layers

See Also:

Serialized Form

Method Summary

Modifier and Type	Method and Description
MultilayerPerceptronClassificationModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
int[]	layers()
static MultilayerPerceptronClassificationModel	load(String path)
int	numClasses() Number of classes (values which the label can take).
int	numFeatures() Returns the number of features the model was trained on.
double	predict(Vector features) Predict label for the given features.
static MLReader<MultilayerPerceptronClassificationModel>	read()
String	uid() An immutable unique ID for the object and its derivatives.
Vector	weights()
MLWriter	write() Returns an MLWriter instance for this ML instance.

Methods inherited from class org.apache.spark.ml.classification.ProbabilisticClassificationModel

normalizeToProbabilitiesInPlace, setProbabilityCol, setThresholds, transform

Methods inherited from class org.apache.spark.ml.classification.ClassificationModel

setRawPredictionCol

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

setFeaturesCol, setPredictionCol, transformSchema

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.util.MLWritable

save

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

validateAndTransformSchema

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

getLabelCol, labelCol

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

featuresCol, getFeaturesCol

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

getPredictionCol, predictionCol

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.HasRawPredictionCol

getRawPredictionCol, rawPredictionCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasProbabilityCol

getProbabilityCol, probabilityCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasThresholds

getThresholds, thresholds

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<MultilayerPerceptronClassificationModel> read()

load

public static MultilayerPerceptronClassificationModel load(String path)

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)

layers

public int[] layers()

weights

public Vector weights()

numFeatures

public int numFeatures()

Description copied from class: PredictionModel

Returns the number of features the model was trained on. If unknown, returns -1

Overrides:

numFeatures in class PredictionModel<Vector,MultilayerPerceptronClassificationModel>

predict

public double predict(Vector features)

Predict label for the given features. This internal method is used to implement transform() and output predictionCol.

Overrides:

predict in class ClassificationModel<Vector,MultilayerPerceptronClassificationModel>

Parameters:

features - (undocumented)

Returns:

(undocumented)

copy

public MultilayerPerceptronClassificationModel 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<MultilayerPerceptronClassificationModel>

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)

numClasses

public int numClasses()

Description copied from class: ClassificationModel

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

Specified by:

numClasses in class ClassificationModel<Vector,MultilayerPerceptronClassificationModel>