public class RidgeRegression extends Object implements Serializable
Constructor and Description |
---|
RidgeRegression() |
Modifier and Type | Method and Description |
---|---|
org.apache.spark.api.java.JavaRDD<scala.Tuple2<Double,Double>> |
test(org.apache.spark.mllib.regression.RidgeRegressionModel ridgeRegressionModel,
org.apache.spark.api.java.JavaRDD<org.apache.spark.mllib.regression.LabeledPoint> testingDataset)
This method applies ridge regression using a given model and a dataset
|
org.apache.spark.mllib.regression.RidgeRegressionModel |
train(org.apache.spark.api.java.JavaRDD<org.apache.spark.mllib.regression.LabeledPoint> trainingDataset,
int noOfIterations,
double initialLearningRate,
double regularizationParameter,
double miniBatchFraction)
This method uses stochastic gradient descent (SGD) algorithm to train a ridge regression model
|
public org.apache.spark.mllib.regression.RidgeRegressionModel train(org.apache.spark.api.java.JavaRDD<org.apache.spark.mllib.regression.LabeledPoint> trainingDataset, int noOfIterations, double initialLearningRate, double regularizationParameter, double miniBatchFraction)
trainingDataset
- Training dataset as a JavaRDD of LabeledPointsnoOfIterations
- Number of iterarationsinitialLearningRate
- Initial learning rate (SGD step size)regularizationParameter
- Regularization parameterminiBatchFraction
- SGD minibatch fractionpublic org.apache.spark.api.java.JavaRDD<scala.Tuple2<Double,Double>> test(org.apache.spark.mllib.regression.RidgeRegressionModel ridgeRegressionModel, org.apache.spark.api.java.JavaRDD<org.apache.spark.mllib.regression.LabeledPoint> testingDataset)
ridgeRegressionModel
- Ridge regression modeltestingDataset
- Testing dataset as a JavaRDD of LabeledPointsCopyright © 2016 WSO2, Inc.. All Rights Reserved.