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resubEdge

Class: ClassificationEnsemble

Classification edge by resubstitution

Syntax

edge = resubEdge(ens)
edge = resubEdge(ens,Name,Value)

Description

edge = resubEdge(ens) returns the classification edge obtained by ens on its training data.

edge = resubEdge(ens,Name,Value) calculates edge with additional options specified by one or more Name,Value pair arguments. You can specify several name-value pair arguments in any order as Name1,Value1,…,NameN,ValueN.

Input Arguments

ens

A classification ensemble created with fitensemble.

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside single quotes (' '). You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

'learners'

Indices of weak learners in the ensemble ranging from 1 to NumTrained. resubEdge uses only these learners for calculating edge.

Default: 1:NumTrained

'mode'

Character vector representing the meaning of the output edge:

  • 'ensemble'edge is a scalar value, the loss for the entire ensemble.

  • 'individual'edge is a vector with one element per trained learner.

  • 'cumulative'edge is a vector in which element J is obtained by using learners 1:J from the input list of learners.

Default: 'ensemble'

Output Arguments

edge

Classification edge obtained by ens by resubstituting the training data into the calculation of edge. Classification edge is classification margin averaged over the entire data. edge can be a scalar or vector, depending on the setting of the mode name-value pair.

Examples

Find the resubstitution edge for an ensemble that classifies the Fisher iris data:

load fisheriris
ens = fitensemble(meas,species,'AdaBoostM2',100,'Tree');
edge = resubEdge(ens)

edge =
    3.2486

Definitions

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