public class BinaryLogisticRegressionSummaryImpl extends LogisticRegressionSummaryImpl implements BinaryLogisticRegressionSummary
param: predictions dataframe output by the model's transform
method.
param: probabilityCol field in "predictions" which gives the probability of
each class as a vector.
param: predictionCol field in "predictions" which gives the prediction of
each class as a double.
param: labelCol field in "predictions" which gives the true label of each instance.
param: featuresCol field in "predictions" which gives the features of each instance as a vector.
param: weightCol field in "predictions" which gives the weight of each instance.
Constructor and Description |
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BinaryLogisticRegressionSummaryImpl(Dataset<Row> predictions,
String probabilityCol,
String predictionCol,
String labelCol,
String featuresCol,
String weightCol) |
Modifier and Type | Method and 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.
|
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.
|
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.
|
featuresCol, labelCol, predictionCol, predictions, probabilityCol, weightCol
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
scoreCol
asBinary, featuresCol, probabilityCol
accuracy, falsePositiveRateByLabel, fMeasureByLabel, fMeasureByLabel, labelCol, labels, precisionByLabel, predictionCol, predictions, recallByLabel, truePositiveRateByLabel, weightCol, weightedFalsePositiveRate, weightedFMeasure, weightedFMeasure, weightedPrecision, weightedRecall, weightedTruePositiveRate
public double areaUnderROC()
BinaryClassificationSummary
areaUnderROC
in interface BinaryClassificationSummary
public Dataset<Row> fMeasureByThreshold()
BinaryClassificationSummary
fMeasureByThreshold
in interface BinaryClassificationSummary
public Dataset<Row> pr()
BinaryClassificationSummary
pr
in interface BinaryClassificationSummary
public Dataset<Row> precisionByThreshold()
BinaryClassificationSummary
precisionByThreshold
in interface BinaryClassificationSummary
public Dataset<Row> recallByThreshold()
BinaryClassificationSummary
recallByThreshold
in interface BinaryClassificationSummary
public Dataset<Row> roc()
BinaryClassificationSummary
roc
in interface BinaryClassificationSummary