Statistics shoud be computed on the same features as the one you use for
the training (in your case you'll need mean and variance for all geometric
features).

Note also that statistics are used to normalize samples between [0,1] to
deal with features with different amplitude. Nevertheless this is not
mandatory for all classifiers. For instead it is not mandatory for random
forests classifier.

Check this article which explains this in more detail:

http://jordiinglada.net/wp/2015/04/22/should-we-always-normalize-image-features-before-classification/

Le jeu. 13 déc. 2018 à 09:01, Friederike Lambrecht <[email protected]>
a écrit :

> I want to include the geometric features (flat, round, elong, perim) that
> I generated with ObjectRadiometricStatistics as features to train the
> classifier for an Object based classification. It works when I only use
> mean and variance as usual.The xml file was created with 
> ComputeOGRLayersFeaturesStatistics
> also including the geometric features.
>
> But I get this Error message:
>
> 2018-12-13 14:29:43 (FATAL): itk::ERROR:
> ShiftScaleSampleListFilter(000002DEDDA15100): Inconsistent measurement
> vector size : Input Sample List size 12 Scale measurement vector size 14
> Shift measurement vector size 14
>
> Does someone know, what could be the problem?
>
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-- 
Manuel Grizonnet

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