jsat.classifiers.trees

Interface TreeFeatureImportanceInference

All Superinterfaces:

Serializable

All Known Implementing Classes:

ImportanceByUses, MDA, MDI

public interface TreeFeatureImportanceInference
extends Serializable

This interface exists for implementing the importance of features from tree based models.

Author:

Edward Raff

Method Summary

Modifier and Type	Method and Description
<Type extends DataSet> double[]	getImportanceStats(TreeLearner model, DataSet<Type> data)

Method Detail

getImportanceStats

<Type extends DataSet> double[] getImportanceStats(TreeLearner model,
                                                   DataSet<Type> data)

Type Parameters:

Type -

Parameters:

model - the tree model to infer feature importance from

data - the dataset to use for importance inference. Should be either a Classification or Regression dataset, depending on the type of the model.

Returns:

a double array with one entry for each feature. Numeric features start first, followed by categorical features. Larger values indicate higher importance, and all values must be non-negative. Otherwise, no constraints are placed on the output of this function.