org.apache.spark.ml.classification

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

java.lang.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>

All Implemented Interfaces:

java.io.Serializable, Logging, Params, Identifiable

Direct Known Subclasses:

ProbabilisticClassificationModel

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

:: DeveloperApi ::

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
Param<java.lang.String>	featuresCol() Param for features column name.
java.lang.String	getFeaturesCol()
java.lang.String	getLabelCol()
java.lang.String	getPredictionCol()
java.lang.String	getRawPredictionCol()
Param<java.lang.String>	labelCol() Param for label column name.
abstract int	numClasses() Number of classes (values which the label can take).
protected double	predict(FeaturesType features) Predict label for the given features.
Param<java.lang.String>	predictionCol() Param for prediction column name.
protected abstract Vector	predictRaw(FeaturesType features) Raw prediction for each possible label.
protected double	raw2prediction(Vector rawPrediction) Given a vector of raw predictions, select the predicted label.
Param<java.lang.String>	rawPredictionCol() Param for raw prediction (a.k.a.
M	setRawPredictionCol(java.lang.String value)
DataFrame	transform(DataFrame dataset) 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.
StructType	validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
StructType	validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType) Validates and transforms the input schema with the provided param map.

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

featuresDataType, numFeatures, setFeaturesCol, setPredictionCol, transformImpl, transformSchema

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

copy, hasParent, parent, setParent

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

transform, transform, transform

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

transformSchema

Methods inherited from class java.lang.Object

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

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

clear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn, validateParams

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

toString, uid

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

setRawPredictionCol

public M setRawPredictionCol(java.lang.String value)

numClasses

public abstract int numClasses()

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

transform

public DataFrame transform(DataFrame dataset)

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

Returns:

transformed dataset

predict

protected double predict(FeaturesType features)

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

This default implementation for classification predicts the index of the maximum value from predictRaw().

Specified by:

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

Parameters:

features - (undocumented)

Returns:

(undocumented)

predictRaw

protected abstract Vector predictRaw(FeaturesType features)

Raw prediction for each possible label. The meaning of a "raw" prediction may vary between algorithms, but it intuitively gives a measure of confidence in each possible label (where larger = more confident). This internal method is used to implement transform() and output rawPredictionCol.

Parameters:

features - (undocumented)

Returns:

vector where element i is the raw prediction for label i. This raw prediction may be any real number, where a larger value indicates greater confidence for that label.

raw2prediction

protected double raw2prediction(Vector rawPrediction)

Given a vector of raw predictions, select the predicted label. This may be overridden to support thresholds which favor particular labels.

Parameters:

rawPrediction - (undocumented)

Returns:

predicted label

validateAndTransformSchema

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

rawPredictionCol

public Param<java.lang.String> rawPredictionCol()

Param for raw prediction (a.k.a. confidence) column name.

Returns:

(undocumented)

getRawPredictionCol

public java.lang.String getRawPredictionCol()

validateAndTransformSchema

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

Validates and transforms the input schema with the provided param map.

Parameters:

schema - input schema

fitting - whether this is in fitting

featuresDataType - SQL DataType for FeaturesType. E.g., VectorUDT for vector features.

Returns:

output schema

labelCol

public Param<java.lang.String> labelCol()

Param for label column name.

Returns:

(undocumented)

getLabelCol

public java.lang.String getLabelCol()

featuresCol

public Param<java.lang.String> featuresCol()

Param for features column name.

Returns:

(undocumented)

getFeaturesCol

public java.lang.String getFeaturesCol()

predictionCol

public Param<java.lang.String> predictionCol()

Param for prediction column name.

Returns:

(undocumented)

getPredictionCol

public java.lang.String getPredictionCol()