Package org.apache.spark.ml.regression

Class LinearRegressionTrainingSummary

Object

org.apache.spark.ml.regression.LinearRegressionSummary

org.apache.spark.ml.regression.LinearRegressionTrainingSummary

All Implemented Interfaces:

Serializable, Summary

public class LinearRegressionTrainingSummary
extends LinearRegressionSummary

Linear regression training results. Currently, the training summary ignores the training weights except for the objective trace.

param: predictions predictions output by the model's transform method. param: objectiveHistory objective function (scaled loss + regularization) at each iteration. param: coefficientArray Coefficients of the linear regression model, only necessary when diagInvAtWA is not Array(0).

See Also:

• Serialized Form

Method Summary

Modifier and Type	Method	Description
double[]	objectiveHistory()
int	totalIterations()	Number of training iterations until termination

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

coefficientStandardErrors, degreesOfFreedom, devianceResiduals, explainedVariance, featuresCol, labelCol, meanAbsoluteError, meanSquaredError, numInstances, predictionCol, predictions, pValues, r2, r2adj, residuals, rootMeanSquaredError, tValues

Methods inherited from class java.lang.Object

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

Method Details

objectiveHistory

public double[] objectiveHistory()

totalIterations

public int totalIterations()

Number of training iterations until termination

This value is only available when using the "l-bfgs" solver.

Returns:

(undocumented)

See Also:

• LinearRegression.solver