org.apache.spark.ml.regression

Class LinearRegressionTrainingSummary

java.lang.Object

org.apache.spark.ml.regression.LinearRegressionSummary

org.apache.spark.ml.regression.LinearRegressionTrainingSummary

All Implemented Interfaces:

java.io.Serializable

public class LinearRegressionTrainingSummary
extends LinearRegressionSummary

:: Experimental :: Linear regression training results. param: predictions predictions outputted by the model's transform method. param: objectiveHistory objective function (scaled loss + regularization) at each iteration.

See Also:

Serialized Form

Method Summary

Methods

Modifier and Type	Method and Description
java.lang.String	featuresCol()
double[]	objectiveHistory()
int	totalIterations() Number of training iterations until termination

Methods inherited from class org.apache.spark.ml.regression.LinearRegressionSummary

explainedVariance, labelCol, meanAbsoluteError, meanSquaredError, predictionCol, predictions, r2, residuals, rootMeanSquaredError

Methods inherited from class java.lang.Object

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

Method Detail

featuresCol

public java.lang.String featuresCol()

objectiveHistory

public double[] objectiveHistory()

totalIterations

public int totalIterations()

Number of training iterations until termination