ROC of multiclass classification in MATLAB

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Chenhui 2015-6-11

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评论： Ismat Mohd Sulaiman 2021-8-9

Hi, guys,

I just used the AdaBoost.M2 in a dataset with four-class response variable. I want to produce the ROC curve. The documentation uses the 'plotroc(targets, outputs)' to do it. My question is about the argument of 'outputs'. The documentation says "S-by-Q matrix, where each column contains values in the range [0,1]. The index of the largest element in the column indicates which of S categories that vector presents. ". How to determine the 'outputs' with the results of AdaBoost.M2?

Another question about the '[X,Y] = perfcurve(labels,scores,posclass) '. What is the 'scores' for a AdaBoos.M2 model?

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mehbob ali 2017-12-28

i want to know how you implemented Adaboost.M2

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Answer 1

Alka Nair 2015-6-17

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Hi, The PERFCURVE function can be used to plot the ROC for AdaBoostM2. Please see the documentation of function PREDICT, to understand what score referes to for ensemble:

http://in.mathworks.com/help/stats/compactclassificationensemble.predict.html?searchHighlight=adaboostm2%20predict

It is mentioned that, for ensembles, a classification score represents the confidence of a classification into a class. The higher the score, the higher the confidence.

The documentation of PERFCURVE mentions that perfcurve can be used with any classifier or, more broadly, with any method that returns a numeric score for an instance of input data. Please refer to the following page for more information:

http://in.mathworks.com/help/stats/performance-curves.html