[Biomod-commits] Error in ensemble by algorithm
Wilfried Thuiller
wilfried.thuiller at ujf-grenoble.fr
Mon Mar 11 07:15:59 CET 2013
Dear Josep,
Please make sure to use the latest version (2.1.13). From the what is pasted below, it seems that the minimum threshold to select the models for the ensemble forecast is too high and no models are selected.
Try to put 0.4 for instance and run the script again.
Best regards,
Wilfried
Le 10 mars 2013 à 20:20, Josep M Serra diaz a écrit :
> Dear BIOMODers,
>
> I found an error while trying to perform modeling ensemble by algorithm in
> order to produce an output for each statistical technique
>
>
> Any clue of what does this mean???
>
> The strane
>
>
> ########################
>
> #ensemble through algorithm
> myBiomodEM.algo <- BIOMOD_EnsembleModeling (
> em.by="algo" ,
> modeling.output = myBiomodModelOut,
> chosen.models = 'all',
> eval.metric = 'TSS',
> eval.metric.quality.threshold =
> c(0.6),
> prob.mean=T,
> prob.cv = T,
> prob.ci = T,
> prob.ci.alpha = 0.05,
> prob.median = T,
> committee.averaging = T,
> prob.mean.weight = F,
> prob.mean.weight.decay =
> 'proportional'
> )
>
>
> -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
> Build Ensemble Models
> -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
>
> ! all models available will be included in ensemble.modeling
>> Evaluation & Weighting methods summary :
> TSS over 0.6
>
>
>> GLM_AllRun ensemble modeling
>> TSS
> ! No models kept due to treshold filtering... Ensemble Modeling was skip!
>
>> GBM_AllRun ensemble modeling
>> TSS
> ! No models kept due to treshold filtering... Ensemble Modeling was skip!
>
>> GAM_AllRun ensemble modeling
>> TSS
> ! No models kept due to treshold filtering... Ensemble Modeling was skip!
>
>> CTA_AllRun ensemble modeling
>> TSS
> ! No models kept due to treshold filtering... Ensemble Modeling was skip!
>
>> ANN_AllRun ensemble modeling
>> TSS
> ! No models kept due to treshold filtering... Ensemble Modeling was skip!
>
>> FDA_AllRun ensemble modeling
>> TSS
> ! No models kept due to treshold filtering... Ensemble Modeling was skip!
>
>> MARS_AllRun ensemble modeling
>> TSS
> ! No models kept due to treshold filtering... Ensemble Modeling was skip!
>
>> RF_AllRun ensemble modeling
>> TSS
>> models kept : Quercusilex_AllData_RUN2_RF
> ! Models projections for whole zonation required...
>> Projecting Quercusilex_AllData_RUN2_RF ...
>
>> Mean of probabilities...
>> Coef of variation of probabilities...
>> Median of ptobabilities...
>> Confidence Interval...
>> 2.5 %
>> 97.5 %
>> Comittee averaging...Warning in FUN(c("KAPPA", "TSS", "ROC", "FAR",
> "SR", "ACCURACY", "BIAS", :
>
> Observed or fited data contains a unique value.. Be carefull with this
> models predictions
>
> Warning in FUN(c("KAPPA", "TSS", "ROC", "FAR", "SR", "ACCURACY", "BIAS", :
>
> Observed or fited data contains a unique value.. Be carefull with this
> models predictions
>
> Warning in FUN(c("KAPPA", "TSS", "ROC", "FAR", "SR", "ACCURACY", "BIAS", :
>
> Observed or fited data contains a unique value.. Be carefull with this
> models predictions
>
> *Error in roc.default(Obs, Fit, percent = T) : No control observation.*
> In addition: There were 50 or more warnings (use warnings() to see the
> first 50)
>> warnings()
> Warning messages:
> 1: In (forecast_1 * observed_1) + (forecast_0 * observed_0) :
> NAs produced by integer overflow
> 2: In (forecast_1 * observed_1) + (forecast_0 * observed_0) :
> NAs produced by integer overflow
> 3: In (forecast_1 * observed_1) + (forecast_0 * observed_0) :
> NAs produced by integer overflow
> 4: In (forecast_1 * observed_1) + (forecast_0 * observed_0) :
> NAs produced by integer overflow
> 5: In forecast_0 * observed_0 : NAs produced by integer overflow
> 6: In forecast_0 * observed_0 : NAs produced by integer overflow
> 7: In forecast_0 * observed_0 : NAs produced by integer overflow
> 8: In forecast_0 * observed_0 : NAs produced by integer overflow
> 9: In forecast_0 * observed_0 : NAs produced by integer overflow
> 10: In forecast_0 * observed_0 : NAs produced by integer overflow
> 11: In forecast_0 * observed_0 : NAs produced by integer overflow
> 12: In forecast_0 * observed_0 : NAs produced by integer overflow
> 13: In forecast_0 * observed_0 : NAs produced by integer overflow
> 14: In forecast_0 * observed_0 : NAs produced by integer overflow
> 15: In forecast_0 * observed_0 : NAs produced by integer overflow
> 16: In forecast_0 * observed_0 : NAs produced by integer overflow
> 17: In forecast_0 * observed_0 : NAs produced by integer overflow
> 18: In forecast_0 * observed_0 : NAs produced by integer overflow
> 19: In forecast_0 * observed_0 : NAs produced by integer overflow
> 20: In forecast_0 * observed_0 : NAs produced by integer overflow
> 21: In forecast_0 * observed_0 : NAs produced by integer overflow
> 22: In forecast_0 * observed_0 : NAs produced by integer overflow
> 23: In forecast_0 * observed_0 : NAs produced by integer overflow
> 24: In forecast_0 * observed_0 : NAs produced by integer overflow
> 25: In forecast_0 * observed_0 : NAs produced by integer overflow
> 26: In forecast_0 * observed_0 : NAs produced by integer overflow
> 27: In forecast_0 * observed_0 : NAs produced by integer overflow
> 28: In forecast_0 * observed_0 : NAs produced by integer overflow
> 29: In forecast_0 * observed_0 : NAs produced by integer overflow
> 30: In forecast_0 * observed_0 : NAs produced by integer overflow
> 31: In forecast_0 * observed_0 : NAs produced by integer overflow
> 32: In forecast_0 * observed_0 : NAs produced by integer overflow
> 33: In forecast_0 * observed_0 : NAs produced by integer overflow
> 34: In forecast_0 * observed_0 : NAs produced by integer overflow
> 35: In forecast_0 * observed_0 : NAs produced by integer overflow
> 36: In forecast_0 * observed_0 : NAs produced by integer overflow
> 37: In forecast_0 * observed_0 : NAs produced by integer overflow
> 38: In forecast_0 * observed_0 : NAs produced by integer overflow
> 39: In forecast_0 * observed_0 : NAs produced by integer overflow
> 40: In forecast_0 * observed_0 : NAs produced by integer overflow
> 41: In forecast_0 * observed_0 : NAs produced by integer overflow
> 42: In forecast_0 * observed_0 : NAs produced by integer overflow
> 43: In forecast_0 * observed_0 : NAs produced by integer overflow
> 44: In forecast_0 * observed_0 : NAs produced by integer overflow
> 45: In forecast_0 * observed_0 : NAs produced by integer overflow
> 46: In forecast_0 * observed_0 : NAs produced by integer overflow
> 47: In forecast_0 * observed_0 : NAs produced by integer overflow
> 48: In forecast_0 * observed_0 : NAs produced by integer overflow
> 49: In forecast_0 * observed_0 : NAs produced by integer overflow
> 50: In forecast_0 * observed_0 : NAs produced by integer overflow
> _______________________________________________
> Biomod-commits mailing list
> Biomod-commits at lists.r-forge.r-project.org
> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/biomod-commits
--------------------------
Dr. Wilfried Thuiller
Laboratoire d'Ecologie Alpine, UMR CNRS 5553
Université Joseph Fourier
BP53, 38041 Grenoble cedex 9, France
tel: +33 (0)4 76 51 44 97
fax: +33 (0)4 76 51 42 79
Email: wilfried.thuiller at ujf-grenoble.fr
Personal website: http://www.will.chez-alice.fr
Team website: http://www-leca.ujf-grenoble.fr/equipes/emabio.htm
ERC Starting Grant TEEMBIO project: http://www.will.chez-alice.fr/Research.html
FP6 European EcoChange project: http://www.ecochange-project.eu
More information about the Biomod-commits
mailing list