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Resubstitution classification margins for discriminant analysis classifier



    m = resubMargin(Mdl) returns the resubstitution classification margins values m for the trained discriminant analysis classifier Mdl using the training data stored in Mdl.X and the corresponding true class labels stored in Mdl.Y. m is returned as a numeric column vector with the same length as Mdl.Y. The software estimates each entry of m using the trained discriminant analysis classifier Mdl, the corresponding row of Mdl.X, and the true class label Mdl.Y.


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    Find the margins for a discriminant analysis classifier for Fisher's iris data by resubstitution. Examine several entries.

    Load Fisher's iris data set.

    load fisheriris

    Train a discriminant analysis classifier.

    Mdl = fitcdiscr(meas,species);

    Compute the resubstitution margins, and display several of them.

    m = resubMargin(Mdl);
    ans = 6×1

    Input Arguments

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    Discriminant analysis classifier, specified as a ClassificationDiscriminant model object trained with fitcdiscr.

    More About

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    Classification Margin

    The classification margin is the difference between the classification score for the true class and maximal classification score for the false classes.

    The classification margin is a column vector with the same number of rows as in the matrix X. A high value of margin indicates a more reliable prediction than a low value.


    For discriminant analysis, the score of a classification is the posterior probability of the classification. For the definition of posterior probability in discriminant analysis, see Posterior Probability.

    Version History

    Introduced in R2011b

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