Package org.apache.spark.ml.regression

Class LinearRegressionModel

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

org.apache.spark.ml.Model<M>

org.apache.spark.ml.PredictionModel<FeaturesType,M>

org.apache.spark.ml.regression.RegressionModel<Vector,LinearRegressionModel>

org.apache.spark.ml.regression.LinearRegressionModel

All Implemented Interfaces:

Serializable, org.apache.spark.internal.Logging, Params, HasAggregationDepth, HasElasticNetParam, HasFeaturesCol, HasFitIntercept, HasLabelCol, HasLoss, HasMaxBlockSizeInMB, HasMaxIter, HasPredictionCol, HasRegParam, HasSolver, HasStandardization, HasTol, HasWeightCol, PredictorParams, LinearRegressionParams, GeneralMLWritable, HasTrainingSummary<LinearRegressionTrainingSummary>, Identifiable, MLWritable

public class LinearRegressionModel
extends RegressionModel<Vector,LinearRegressionModel>
implements LinearRegressionParams, GeneralMLWritable, HasTrainingSummary<LinearRegressionTrainingSummary>

Model produced by LinearRegression.

See Also:

• Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter

Method Summary

Modifier and Type	Method	Description
final IntParam	aggregationDepth()	Param for suggested depth for treeAggregate (>= 2).
Vector	coefficients()
LinearRegressionModel	copy(ParamMap extra)	Creates a copy of this instance with the same UID and some extra params.
final DoubleParam	elasticNetParam()	Param for the ElasticNet mixing parameter, in range [0, 1].
final DoubleParam	epsilon()	The shape parameter to control the amount of robustness.
LinearRegressionSummary	evaluate(Dataset<?> dataset)	Evaluates the model on a test dataset.
final BooleanParam	fitIntercept()	Param for whether to fit an intercept term.
double	intercept()
static LinearRegressionModel	load(String path)
final Param<String>	loss()	The loss function to be optimized.
final DoubleParam	maxBlockSizeInMB()	Param for Maximum memory in MB for stacking input data into blocks.
final IntParam	maxIter()	Param for maximum number of iterations (&gt;= 0).
int	numFeatures()	Returns the number of features the model was trained on.
double	predict(Vector features)	Predict label for the given features.
static MLReader<LinearRegressionModel>	read()
final DoubleParam	regParam()	Param for regularization parameter (&gt;= 0).
double	scale()
final Param<String>	solver()	The solver algorithm for optimization.
final BooleanParam	standardization()	Param for whether to standardize the training features before fitting the model.
LinearRegressionTrainingSummary	summary()	Gets summary (e.g.
final DoubleParam	tol()	Param for the convergence tolerance for iterative algorithms (&gt;= 0).
String	toString()
String	uid()	An immutable unique ID for the object and its derivatives.
final Param<String>	weightCol()	Param for weight column name.
GeneralMLWriter	write()	Returns a GeneralMLWriter instance for this ML instance.

Methods inherited from class org.apache.spark.ml.PredictionModel

featuresCol, labelCol, predictionCol, setFeaturesCol, setPredictionCol, transform, transformSchema

Methods inherited from class org.apache.spark.ml.Model

hasParent, parent, setParent

Methods inherited from class org.apache.spark.ml.Transformer

transform, transform, transform

Methods inherited from class org.apache.spark.ml.PipelineStage

params

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.apache.spark.ml.param.shared.HasAggregationDepth

getAggregationDepth

Methods inherited from interface org.apache.spark.ml.param.shared.HasElasticNetParam

getElasticNetParam

Methods inherited from interface org.apache.spark.ml.param.shared.HasFeaturesCol

featuresCol, getFeaturesCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasFitIntercept

getFitIntercept

Methods inherited from interface org.apache.spark.ml.param.shared.HasLabelCol

getLabelCol,