[GRASS-user] v.class.mlR Error in data.frame : arguments imply differing number of rows

Jamille Haarloo j.r.haarloo at gmail.com
Tue Apr 16 05:37:10 PDT 2019


Hi Moritz,

Thank you! it worked.

I did not find the line nor similar lines of 'features <-
na.omit(features)' in the v.class.mlR script/ R_script4 file.

Best,
Jamille

On Mon, Apr 15, 2019 at 11:09 AM Moritz Lennert <
mlennert at club.worldonline.be> wrote:

> Hi Jamille,
>
> On 15/04/19 14:49, Jamille Haarloo wrote:> Dear Moritz and other Grass-
> users and developers,
>  >
>  > I tried dealing with the error myself by changing predicted <-
>  > data.frame(predict(models.cv <http://models.cv>, features)) into
>  > predicted <- data.frame(predict(models.cv <http://models.cv>, features,
>  > na.action = na.exclude)), based on discussions online implying some
>  > predictions might be invalid NaN values. I checked the script output to
>  > see if this change was implemented and it was, but I get the same error.
>  > Any suggestions what to try next?>
>  > ------------------------------
>  > v.class.mlR -i --overwrite segments_map=nvSegW24IDM4DV4 at LUP1
>  > training_map=TrainingApril2019 at LUP1 train_class_column=class_code
>  > output_class_column=output_class output_prob_column=probability
>  > classifiers=svmLinear,rf,xgbTree folds=5 partitions=10 tunelength=10
>  > weighting_modes=bwwv,qbwwv weighting_metric=accuracy
>  >
> classification_results=C:\Users\haarlooj\Documents\CELOS\v.class.mlr_outputapril2019\results_all_classifiers
>
>
>  >
> accuracy_file=C:\Users\haarlooj\Documents\CELOS\v.class.mlr_outputapril2019\accuracy_classifiers
>
>
>  >
> model_details=C:\Users\haarlooj\Documents\CELOS\v.class.mlr_outputapril2019\details_classifier_module_runs
>
>
>  >
> bw_plot_file=C:\Users\haarlooj\Documents\CELOS\v.class.mlr_outputapril2019\box-whicker_classifier_performance
>
>
>  >
> r_script_file=C:\Users\haarlooj\Documents\CELOS\v.class.mlr_outputapril2019\R_script4
>
>
>  > processes=3
> Normally, there should be no NA in the features as there is a line:
>
> features <- na.omit(features)
>
> early in the R script. Can you see it in the R_script4 file ?
>
>
>  > Running R now. Following output is R output.
>  > During startup - Warning messages:
>  > 1: Setting LC_CTYPE=en_US.cp1252 failed
>  > 2: Setting LC_COLLATE=en_US.cp1252 failed
>  > 3: Setting LC_TIME=en_US.cp1252 failed
>  > 4: Setting LC_MONETARY=en_US.cp1252 failed
>  > Loading required package: caret
>  > Loading required package: lattice
>  > Loading required package: ggplot2
>  > Warning messages:
>  > 1: package 'caret' was built under R version 3.5.3
>  > 2: package 'ggplot2' was built under R version 3.5.3
>  > Loading required package: foreach
>  > Loading required package: iterators
>  > Loading required package: parallel
>  > Warning messages:
>  > 1: package 'doParallel' was built under R version 3.5.3
>  > 2: package 'foreach' was built under R version 3.5.3
>  > 3: package 'iterators' was built under R version 3.5.3
>  > During startup - Warning messages:
>  > 1: Setting LC_CTYPE=en_US.cp1252 failed
>  > 2: Setting LC_COLLATE=en_US.cp1252 failed
>  > 3: Setting LC_TIME=en_US.cp1252 failed
>  > 4: Setting LC_MONETARY=en_US.cp1252 failed
>  > During startup - Warning messages:
>  > 1: Setting LC_CTYPE=en_US.cp1252 failed
>  > 2: Setting LC_COLLATE=en_US.cp1252 failed
>  > 3: Setting LC_TIME=en_US.cp1252 failed
>  > 4: Setting LC_MONETARY=en_US.cp1252 failed
>  > During startup - Warning messages:
>  > 1: Setting LC_CTYPE=en_US.cp1252 failed
>  > 2: Setting LC_COLLATE=en_US.cp1252 failed
>  > 3: Setting LC_TIME=en_US.cp1252 failed
>  > 4: Setting LC_MONETARY=en_US.cp1252 failed
>  > Error in data.frame(id = rownames(features), predicted) :
>  >    arguments imply differing number of rows: 17851, 17849
>  > Execution halted
> IDs are taken from the features and for some reasons there are two
> features which do not have a prediction. It might help if you could find
> out why.
>
> I cannot test right now, but you might want to check if you can replace
>
> ids <- rownames(features)
>
> with something like
>
> ids <- rownames(predicted)
>
> ?
>
> Moritz
>
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