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Mickaël

Le jeu. 28 mai 2020 à 10:40, Bassam <[email protected]> a écrit :

> Hello every one,
> I have a problem with regression applications. I'd like to know if there
> are any workflow, precautions, etc. I was applying the
> TrainRegression/TrainImagesRegression. I used packages from 6.2, 7.0 and 7.1
>
> *for TrainiImagesRegression*:
> The used predictor images are of type float, 30 bands images
> the label image is a float image (how to provide stats file for both of
> them? if I use io.imstat , an error of mismatching size is reproduced!)
>
> *The output model: * contains only 2 classes (I expected too many
> classes, since it is a regression problem). When generating the output
> image (using ImageRegression), it produces a similar to the mask file (an
> roi file with 1s where the regressor should predict the values)
>
> *for TrainRegression*, the training is using the predictor and label
> image, as stated in the documentation as 31 bands (30 for input and last
> band for the lable image). The model wasn't completed, becauuse of error
> related to mse= - nan, as the following:
>
> *Error using 7.1*:
> Mean Square Error = -nan
> Output parameters value:
> io.mse: 3.402823466e+38
>
> *The model file can not be inferred, with the following:*
> svm_type epsilon_svr
> kernel_type rbf
> gamma 1
> nr_class 2
> total_sv 0
> rho -nan
> SV
>
>
> I'd like to know/request also, the following:
> Can I set a gamma parameter to the libsvm parameter set or not? instead of
> search for it using .opt parameter (I did a work around by asigning a
> search grid for gamma with adjacent values, as given in my commend,
> hereinafter)
> Can I scale the data between 0 and 1, rather than normalize the data? (my
> data contains hot encoded classes)
> What is structure of the training and validation vector file (should it
> contain different polygons for different values? as an analogy with a
> classification problem)
> Could we have documentation for model file structure?
>
> my command looks like: (I couldn't use the io.imstat file becuase it give
> error, it appears that the application uses the same xml file to scale the
> predictor and label image)
>
> otbcli_TrainImagesRegression -io.il pfile1.tif pfile2.tif  -io.ip
> lfile1.tif lfile2.tif -io.vd vec1.shp vec2.shp  -io.out Model_svm.txt
> -sample.nt 10000  -sample.type periodic  -ram 8000 -classifier libsvm
> -classifier.libsvm.k rbf -classifier.libsvm.opt 1 -classifier.libsvm.c 1000
> -classifier.libsvm.gamma_grid.min_val 0.001
> -classifier.libsvm.gamma_grid.max_val 0.002
>
> I am grateful for the attention that you may put for this issue.
>
> Thanks
>
>
>
>
>
>
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