org.apache.spark.ml.classification

Interface LogisticRegressionSummary

All Superinterfaces:

java.io.Serializable

All Known Subinterfaces:

LogisticRegressionTrainingSummary

All Known Implementing Classes:

BinaryLogisticRegressionSummary, BinaryLogisticRegressionTrainingSummary

public interface LogisticRegressionSummary
extends scala.Serializable

Abstraction for Logistic Regression Results for a given model.

Method Summary

Methods

Modifier and Type	Method and Description
java.lang.String	featuresCol() Field in "predictions" which gives the features of each instance as a vector.
java.lang.String	labelCol() Field in "predictions" which gives the true label of each instance (if available).
Dataset<Row>	predictions() Dataframe output by the model's `transform` method.
java.lang.String	probabilityCol() Field in "predictions" which gives the probability of each class as a vector.

Method Detail

predictions

Dataset<Row> predictions()

Dataframe output by the model's `transform` method.

probabilityCol

java.lang.String probabilityCol()

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

labelCol

java.lang.String labelCol()

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

featuresCol

java.lang.String featuresCol()

Field in "predictions" which gives the features of each instance as a vector.