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 |
|---|
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, weightColequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitscoreColasBinary, featuresCol, probabilityColaccuracy, falsePositiveRateByLabel, fMeasureByLabel, fMeasureByLabel, labelCol, labels, precisionByLabel, predictionCol, predictions, recallByLabel, truePositiveRateByLabel, weightCol, weightedFalsePositiveRate, weightedFMeasure, weightedFMeasure, weightedPrecision, weightedRecall, weightedTruePositiveRatepublic double areaUnderROC()
BinaryClassificationSummaryareaUnderROC in interface BinaryClassificationSummarypublic Dataset<Row> fMeasureByThreshold()
BinaryClassificationSummaryfMeasureByThreshold in interface BinaryClassificationSummarypublic Dataset<Row> pr()
BinaryClassificationSummarypr in interface BinaryClassificationSummarypublic Dataset<Row> precisionByThreshold()
BinaryClassificationSummaryprecisionByThreshold in interface BinaryClassificationSummarypublic Dataset<Row> recallByThreshold()
BinaryClassificationSummaryrecallByThreshold in interface BinaryClassificationSummarypublic Dataset<Row> roc()
BinaryClassificationSummaryroc in interface BinaryClassificationSummary