org.apache.spark.mllib.regression
Interface RegressionModel

All Superinterfaces:

java.io.Serializable

All Known Implementing Classes:

LassoModel, LinearRegressionModel, RidgeRegressionModel

public interface RegressionModel
extends scala.Serializable

Method Summary

JavaRDD<Double>	predict(JavaRDD<Vector> testData) Predict values for examples stored in a JavaRDD.
RDD<Object>	predict(RDD<Vector> testData) Predict values for the given data set using the model trained.
double	predict(Vector testData) Predict values for a single data point using the model trained.

Method Detail

predict

RDD<Object> predict(RDD<Vector> testData)

Predict values for the given data set using the model trained.

Parameters:

testData - RDD representing data points to be predicted

Returns:

RDD[Double] where each entry contains the corresponding prediction

predict

double predict(Vector testData)

Predict values for a single data point using the model trained.

Parameters:

testData - array representing a single data point

Returns:

Double prediction from the trained model

predict

JavaRDD<Double> predict(JavaRDD<Vector> testData)

Predict values for examples stored in a JavaRDD.

Parameters:

testData - JavaRDD representing data points to be predicted

Returns:

a JavaRDD[java.lang.Double] where each entry contains the corresponding prediction