org.apache.spark.mllib.classification

Interface ClassificationModel

All Superinterfaces:

java.io.Serializable

All Known Implementing Classes:

LogisticRegressionModel, NaiveBayesModel, SVMModel

public interface ClassificationModel
extends scala.Serializable

Represents a classification model that predicts to which of a set of categories an example belongs. The categories are represented by double values: 0.0, 1.0, 2.0, etc.

Method Summary

Modifier and Type	Method and Description
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:

an 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:

predicted category 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