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R2012a Documentation → Statistics Toolbox
View documentation for other releases	Learn more about Statistics Toolbox

Contents

Index

• Getting Started

• User's Guide

• Data Organization

• Descriptive Statistics

• Statistical Visualization

• Probability Distributions

• Hypothesis Tests

• Analysis of Variance

• Parametric Regression Analysis

• Multivariate Methods

• Cluster Analysis

• Model Assessment

• Parametric Classification

• Nonparametric Supervised Learning

• Distance Computation and Classification by Distance

• Classification Trees

• Regression Trees

• Ensemble Methods — Classification

ClassificationBaggedEnsemble

ClassificationEnsemble

ClassificationPartitionedEnsemble

CompactClassificationEnsemble

CompactTreeBagger

fillProximities

predictorImportance

• Ensemble Methods — Regression

• Hidden Markov Models

• Design of Experiments

• Statistical Process Control

• GUIs

• Release Notes

fillProximities - Class: TreeBagger

Proximity matrix for training data

Syntax

B = fillProximities(B) B = fillProximities(B,'param1',val1,'param2',val2,...

Description

B = fillProximities(B) computes a proximity matrix for the training data and stores it in the Properties field of B.

B = fillProximities(B,'param1',val1,'param2',val2,...) specifies optional parameter name/value pairs:

`'trees'`	Either `'all'` or a vector of indices of the trees in the ensemble to be used in computing the proximity matrix. Default is `'all'`.
`'nprint'`	Number of training cycles (grown trees) after which `TreeBagger` displays a diagnostic message showing training progress. Default is no diagnostic messages.

See Also

CompactTreeBagger.outlierMeasure | CompactTreeBagger.proximity

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