[Biomod-commits] consensus AUC

[Wilfried Thuiller]

Hi Ashley,

I am not quite sure what you really would like to do. 
Do you want to estimate the consensus AUC for the calibrated models? for the final models? for the future? 

In the meantime, given the line of code you wrote for the Ensemble.Forecasting, you should have a printed message with the consensus AUC for the calibrated and final models. 

Something like this the one pasted below. The AUC are in $Sp164$test.results 

$Sp164
$Sp164$weights
         ANN    CTA GAM GBM GLM MARS FDA     RF SRE
PA1        0 0.3846   0   0   0    0   0 0.6154   0
PA1_rep1   0 0.3846   0   0   0    0   0 0.6154   0

$Sp164$PCA.median
         model.selected
PA1      "RF"          
PA1_rep1 "CTA"         

$Sp164$thresholds
                        PA1 PA1_rep1
prob.mean          743.5000 631.3875
prob.mean.weighted 720.0769 568.0673
median             743.5000 631.3875
Roc.mean           500.0000 500.0000
Kappa.mean         500.0000 500.0000
TSS.mean           500.0000 500.0000

$Sp164$test.results
                         PA1  PA1_rep1
prob.mean          0.9994010 0.9948069
prob.mean.weighted 0.9997921 0.9968292
median             0.9994010 0.9948069
Roc.mean           0.9929901 0.9912946
Kappa.mean         0.9993688 0.9921139
TSS.mean           0.9995842 0.9903020



Hope it helps,

Cheers,

Wilfried





Le 3 avr. 2012 à 21:49, Ashley Brooks a écrit :

> Hi all!
> 
> I would like to report the overall AUC value for my ensemble prediction and my question is: where is the consensus AUC output or do I need to calculate this myself?  If I need to calculate manually does the fact that my decay was set to proportional?  Here are my commands thus far:
> 
> > Models(GLM=T, TypeGLM="poly", Test="AIC", GBM=T, No.trees=2000, GAM=T, Spline=3, CTA=T, CV.tree=50, ANN=T, CV.ann=2, SRE=T,quant=0.05, FDA=T, MARS=T, RF=T, NbRunEval=3, DataSplit=70, Yweights=NULL, Roc=T, Optimized.Threshold.Roc=T, Kappa=T, TSS=T, KeepPredIndependent=T, VarImport=5, NbRepPA=2, strategy="circles", coor=Coor, distance=2, nb.absences=1000)
> 
> > Projection(Proj=cccm80a2a[,3:12], Proj.name='cccm80a2a', GLM=T, GBM=T, GAM=T, CTA=T, ANN=T, SRE=T, quant=0.05, FDA=T, MARS=T, RF=T, BinRoc=T, BinKappa=F, BinTSS=F, FiltRoc=T, FiltKappa=F, FiltTSS=F, repetition.models=T)
> 
> > Ensemble.Forecasting(Proj.name="cccm80a2a", weight.method='Roc', PCA.media=F, binary=T, bin.method='Roc', Test=T, decay="proportional", repetition.models=T, final.model.out=TRUE)
> 
> Thanks for your help!
> Ashley
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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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