Package org.apache.spark.ml.classification

Class FMClassificationSummaryImpl

Object

org.apache.spark.ml.classification.FMClassificationSummaryImpl

All Implemented Interfaces:

Serializable, BinaryClassificationSummary, ClassificationSummary, FMClassificationSummary, Summary

Direct Known Subclasses:

FMClassificationTrainingSummaryImpl

public class FMClassificationSummaryImpl
extends Object
implements FMClassificationSummary

FMClassifier results for a given model.

param: predictions dataframe output by the model's transform method. param: scoreCol field in "predictions" which gives the probability of each instance. param: predictionCol field in "predictions" which gives the prediction for a data instance as a double. param: labelCol field in "predictions" which gives the true label of each instance. param: weightCol field in "predictions" which gives the weight of each instance.

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
FMClassificationSummaryImpl(Dataset<Row> predictions, String scoreCol, String predictionCol, String labelCol, String weightCol)

Method Summary

Modifier and Type	Method	Description
double	areaUnderROC()	Computes the area under the receiver operating characteristic (ROC) curve.
Dataset<Row>	fMeasureByThreshold()	Returns a dataframe with two fields (threshold, F-Measure) curve with beta = 1.0.
String	labelCol()	Field in "predictions" which gives the true label of each instance (if available).
Dataset<Row>	pr()	Returns the precision-recall curve, which is a Dataframe containing two fields recall, precision with (0.0, 1.0) prepended to it.
Dataset<Row>	precisionByThreshold()	Returns a dataframe with two fields (threshold, precision) curve.
String	predictionCol()	Field in "predictions" which gives the prediction of each class.
Dataset<Row>	predictions()	Dataframe output by the model's transform method.
Dataset<Row>	recallByThreshold()	Returns a dataframe with two fields (threshold, recall) curve.
Dataset<Row>	roc()	Returns the receiver operating characteristic (ROC) curve, which is a Dataframe having two fields (FPR, TPR) with (0.0, 0.0) prepended and (1.0, 1.0) appended to it.
String	scoreCol()	Field in "predictions" which gives the probability or rawPrediction of each class as a vector.
String	weightCol()	Field in "predictions" which gives the weight of each instance.

Methods inherited from class java.lang.Object

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

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

accuracy, falsePositiveRateByLabel, fMeasureByLabel, fMeasureByLabel, labels, precisionByLabel, recallByLabel, truePositiveRateByLabel, weightedFalsePositiveRate, weightedFMeasure, weightedFMeasure, weightedPrecision, weightedRecall, weightedTruePositiveRate

Constructor Details

FMClassificationSummaryImpl

public FMClassificationSummaryImpl(Dataset<Row> predictions,
 String scoreCol,
 String predictionCol,
 String labelCol,
 String weightCol)

Method Details

areaUnderROC

public double areaUnderROC()

Description copied from interface: BinaryClassificationSummary

Computes the area under the receiver operating characteristic (ROC) curve.

Specified by:

areaUnderROC in interface BinaryClassificationSummary

Returns:

(undocumented)

fMeasureByThreshold

public Dataset<Row> fMeasureByThreshold()

Description copied from interface: BinaryClassificationSummary

Returns a dataframe with two fields (threshold, F-Measure) curve with beta = 1.0.

Specified by:

fMeasureByThreshold in interface BinaryClassificationSummary

Returns:

(undocumented)

labelCol

public String labelCol()

Description copied from interface: ClassificationSummary

Field in "predictions" which gives the true label of each instance (if available).

Specified by:

labelCol in interface ClassificationSummary

pr

public Dataset<Row> pr()

Description copied from interface: BinaryClassificationSummary

Returns the precision-recall curve, which is a Dataframe containing two fields recall, precision with (0.0, 1.0) prepended to it.

Specified by:

pr in interface BinaryClassificationSummary

Returns:

(undocumented)

precisionByThreshold

public Dataset<Row> precisionByThreshold()

Description copied from interface: BinaryClassificationSummary

Returns a dataframe with two fields (threshold, precision) curve. Every possible probability obtained in transforming the dataset are used as thresholds used in calculating the precision.

Specified by:

precisionByThreshold in interface BinaryClassificationSummary

Returns:

(undocumented)

predictionCol

public String predictionCol()

Description copied from interface: ClassificationSummary

Field in "predictions" which gives the prediction of each class.

Specified by:

predictionCol in interface ClassificationSummary

predictions

public Dataset<Row> predictions()

Description copied from interface: ClassificationSummary

Dataframe output by the model's transform method.

Specified by:

predictions in interface ClassificationSummary

Returns:

(undocumented)

recallByThreshold

public Dataset<Row> recallByThreshold()

Description copied from interface: BinaryClassificationSummary

Returns a dataframe with two fields (threshold, recall) curve. Every possible probability obtained in transforming the dataset are used as thresholds used in calculating the recall.

Specified by:

recallByThreshold in interface BinaryClassificationSummary

Returns:

(undocumented)

roc

public Dataset<Row> roc()

Description copied from interface: BinaryClassificationSummary

Returns the receiver operating characteristic (ROC) curve, which is a Dataframe having two fields (FPR, TPR) with (0.0, 0.0) prepended and (1.0, 1.0) appended to it. See http://en.wikipedia.org/wiki/Receiver_operating_characteristic

Specified by:

roc in interface BinaryClassificationSummary

Returns:

(undocumented)

scoreCol

public String scoreCol()

Description copied from interface: BinaryClassificationSummary

Field in "predictions" which gives the probability or rawPrediction of each class as a vector.

Specified by:

scoreCol in interface BinaryClassificationSummary

Returns:

(undocumented)

weightCol

public String weightCol()

Description copied from interface: ClassificationSummary

Field in "predictions" which gives the weight of each instance.

Specified by:

weightCol in interface ClassificationSummary