org.apache.spark.mllib.tree.model

Class RandomForestModel

Object

org.apache.spark.mllib.tree.model.RandomForestModel

All Implemented Interfaces:

java.io.Serializable, Saveable

public class RandomForestModel
extends Object
implements Saveable

Represents a random forest model.

param: algo algorithm for the ensemble model, either Classification or Regression param: trees tree ensembles

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	org.apache.spark.mllib.tree.model.TreeEnsembleModel.SaveLoadV1_0$

Constructor Summary

Constructors

Constructor and Description
RandomForestModel(scala.Enumeration.Value algo, DecisionTreeModel[] trees)

Method Summary

Modifier and Type	Method and Description
scala.Enumeration.Value	algo()
static RandomForestModel	load(SparkContext sc, String path)
int	numTrees() Get number of trees in ensemble.
JavaRDD<Double>	predict(JavaRDD<Vector> features) Java-friendly version of org.apache.spark.mllib.tree.model.TreeEnsembleModel.predict.
RDD<Object>	predict(RDD<Vector> features) Predict values for the given data set.
double	predict(Vector features) Predict values for a single data point using the model trained.
void	save(SparkContext sc, String path) Save this model to the given path.
String	toDebugString() Print the full model to a string.
String	toString() Print a summary of the model.
int	totalNumNodes() Get total number of nodes, summed over all trees in the ensemble.
DecisionTreeModel[]	trees()

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

RandomForestModel

public RandomForestModel(scala.Enumeration.Value algo,
                         DecisionTreeModel[] trees)

Method Detail

load

public static RandomForestModel load(SparkContext sc,
                                     String path)

Parameters:

sc - Spark context used for loading model files.

path - Path specifying the directory to which the model was saved.

Returns:

Model instance

algo

public scala.Enumeration.Value algo()

trees

public DecisionTreeModel[] trees()

save

public void save(SparkContext sc,
                 String path)

Description copied from interface: Saveable

Save this model to the given path.

This saves: - human-readable (JSON) model metadata to path/metadata/ - Parquet formatted data to path/data/

The model may be loaded using Loader.load.

Specified by:

save in interface Saveable

Parameters:

sc - Spark context used to save model data.

path - Path specifying the directory in which to save this model. If the directory already exists, this method throws an exception.

predict

public double predict(Vector features)

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

Parameters:

features - array representing a single data point

Returns:

predicted category from the trained model

predict

public RDD<Object> predict(RDD<Vector> features)

Predict values for the given data set.

Parameters:

features - RDD representing data points to be predicted

Returns:

RDD[Double] where each entry contains the corresponding prediction

predict

public JavaRDD<Double> predict(JavaRDD<Vector> features)

Java-friendly version of org.apache.spark.mllib.tree.model.TreeEnsembleModel.predict.

Parameters:

features - (undocumented)

Returns:

(undocumented)

toString

public String toString()

Print a summary of the model.

Overrides:

toString in class Object

Returns:

(undocumented)

toDebugString

public String toDebugString()

Print the full model to a string.

Returns:

(undocumented)

numTrees

public int numTrees()

Get number of trees in ensemble.

Returns:

(undocumented)

totalNumNodes

public int totalNumNodes()

Get total number of nodes, summed over all trees in the ensemble.

Returns:

(undocumented)