GeneralizedLinearModel (Spark 3.5.5 JavaDoc) (original) (raw)

• Object

• • org.apache.spark.mllib.regression.GeneralizedLinearModel

• All Implemented Interfaces:
  java.io.Serializable
  Direct Known Subclasses:
  LassoModel, LinearRegressionModel, LogisticRegressionModel, RidgeRegressionModel, SVMModel

public abstract class GeneralizedLinearModel
extends Object
implements scala.Serializable
GeneralizedLinearModel (GLM) represents a model trained using GeneralizedLinearAlgorithm. GLMs consist of a weight vector and an intercept.
param: weights Weights computed for every feature. param: intercept Intercept computed for this model.
See Also:
Serialized Form

• • Constructor Summary

  Constructors

  Constructor and Description
  GeneralizedLinearModel(Vector weights, double intercept)

  • Method Summary

  All Methods Instance Methods Concrete Methods

  Modifier and Type	Method and Description
  double	intercept()
  RDD	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.
  String	toString() Print a summary of the model.
  Vector	weights()

     * ### Methods inherited from class Object  
     `equals, getClass, hashCode, notify, notifyAll, wait, wait, wait`

• • Constructor Detail

     * #### GeneralizedLinearModel  
     public GeneralizedLinearModel([Vector](../../../../../org/apache/spark/mllib/linalg/Vector.html "interface in org.apache.spark.mllib.linalg") weights,  
                                   double intercept)  

  • Method Detail

    * #### intercept  
    public double intercept()  
    * #### predict  
    public [RDD](../../../../../org/apache/spark/rdd/RDD.html "class in org.apache.spark.rdd")<Object> predict([RDD](../../../../../org/apache/spark/rdd/RDD.html "class in org.apache.spark.rdd")<[Vector](../../../../../org/apache/spark/mllib/linalg/Vector.html "interface in org.apache.spark.mllib.linalg")> 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  
    public double predict([Vector](../../../../../org/apache/spark/mllib/linalg/Vector.html "interface in org.apache.spark.mllib.linalg") 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  
    * #### toString  
    public String toString()  
    Print a summary of the model.  
    Overrides:  
    `toString` in class `Object`  
    Returns:  
    (undocumented)  
    * #### weights  
    public [Vector](../../../../../org/apache/spark/mllib/linalg/Vector.html "interface in org.apache.spark.mllib.linalg") weights()