[Biomod-commits] Error in ensemble by algorithm
Josep M Serra diaz
pep.bioalerts at gmail.com
Tue Mar 12 09:35:51 CET 2013
Thanx foru your answers, it did work when lowering the quality threshold...
However, it seems that this error came up when the quality threshold only
selects one model (the case of Random forests), than it breaks the
calculation because it cannot be ensembled. It is like biomod2 is prepared
to say ' no models selected' but if 1 model is selected then the error
appears.
It is my impression but I have no clue,
Best,
Pep
2013/3/11 Wilfried Thuiller <wilfried.thuiller at ujf-grenoble.fr>
> 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
> _______________________________________________
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>
>
> --------------------------
> 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
>
>
>
>
>
>
>
>
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