public class LogisticRegressionSummaryImpl extends Object implements LogisticRegressionSummary
 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 for a data instance 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 | 
|---|
| LogisticRegressionSummaryImpl(Dataset<Row> predictions,
                             String probabilityCol,
                             String predictionCol,
                             String labelCol,
                             String featuresCol,
                             String weightCol) | 
| Modifier and Type | Method and Description | 
|---|---|
| String | featuresCol()Field in "predictions" which gives the features of each instance as a vector. | 
| String | labelCol()Field in "predictions" which gives the true label of each instance (if available). | 
| String | predictionCol()Field in "predictions" which gives the prediction of each class. | 
| Dataset<Row> | predictions()Dataframe output by the model's  transformmethod. | 
| String | probabilityCol()Field in "predictions" which gives the probability of each class as a vector. | 
| String | weightCol()Field in "predictions" which gives the weight of each instance. | 
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitasBinaryaccuracy, falsePositiveRateByLabel, fMeasureByLabel, fMeasureByLabel, labels, precisionByLabel, recallByLabel, truePositiveRateByLabel, weightedFalsePositiveRate, weightedFMeasure, weightedFMeasure, weightedPrecision, weightedRecall, weightedTruePositiveRatepublic String featuresCol()
LogisticRegressionSummaryfeaturesCol in interface LogisticRegressionSummarypublic String labelCol()
ClassificationSummarylabelCol in interface ClassificationSummarypublic String predictionCol()
ClassificationSummarypredictionCol in interface ClassificationSummarypublic Dataset<Row> predictions()
ClassificationSummarytransform method.predictions in interface ClassificationSummarypublic String probabilityCol()
LogisticRegressionSummaryprobabilityCol in interface LogisticRegressionSummarypublic String weightCol()
ClassificationSummaryweightCol in interface ClassificationSummary