Package org.apache.spark.mllib.classification

Interface ClassificationModel

All Superinterfaces:
Serializable
All Known Implementing Classes:
LogisticRegressionModel, NaiveBayesModel, SVMModel
public interface ClassificationModel extends 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
    Description
    JavaRDD<Double>
    predict(JavaRDD<Vector> testData)
    Predict values for examples stored in a JavaRDD.
    double
    predict(Vector testData)
    Predict values for a single data point using the model trained.
    RDD<Object>
    predict(RDD<Vector> testData)
    Predict values for the given data set using the model trained.

  • Method Details

    • 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