Question

我必须得到AUC（ROC曲线下面积）来评估我的模型。我正在使用带有Biomod2包的SRE模型。

Biomod2通过 evaluate（）函数给出了AUC值，这很好。然后我尝试用ROCR包检查AUC，我遇到了一个大问题：来自evaluate（）（Biomod2）和ROCR的AUC值不一样。（对于其他一些未在Biomod2上实现的模型，我必须使用ROCR包，这就是我担心的原因。）

现在我正在尝试使用可重现的示例（来自Biomod2包的代码）找到问题，但是我收到了错误。

首先，来自Biomod2包的代码（可重现的例子）：

end

然后，从ROCR获得AUC的部分：

     library(biomod2)
     library(ROCR)

     # species occurrences
     DataSpecies <- read.csv(system.file("external/species/mammals_table.csv",
                                package="biomod2"), row.names = 1)
     head(DataSpecies)

     # the name of studied species
     myRespName <- 'GuloGulo'

     # the presence/absences data for our species 
     myResp <- as.numeric(DataSpecies[,myRespName])

     # the XY coordinates of species data
     myRespXY <- DataSpecies[,c("X_WGS84","Y_WGS84")]


     # Environmental variables extracted from BIOCLIM (bio_3, bio_4,     bio_7, bio_11 & bio_12)
     myExpl = stack( system.file( "external/bioclim/current/bio3.grd", 
                         package="biomod2"),
            system.file( "external/bioclim/current/bio4.grd", 
                         package="biomod2"), 
            system.file( "external/bioclim/current/bio7.grd", 
                         package="biomod2"),  
            system.file( "external/bioclim/current/bio11.grd", 
                         package="biomod2"), 
            system.file( "external/bioclim/current/bio12.grd", 
                         package="biomod2"))

     # 1. Formatting Data
     myBiomodData <- BIOMOD_FormatingData(resp.var = myResp,
                                 expl.var = myExpl,
                                 resp.xy = myRespXY,
                                 resp.name = myRespName)

     # 2. Defining Models Options using default options.
     myBiomodOption <- BIOMOD_ModelingOptions()

     # 3. Doing Modelisation

     myBiomodModelOut <- BIOMOD_Modeling( myBiomodData, 
                                 models = c('SRE'), 
                                 models.options = myBiomodOption, 
                                 NbRunEval=1, 
                                 DataSplit=80, 
                                 Yweights=NULL, 
                                 VarImport=3, 
                                 models.eval.meth = c('TSS'),
                                 SaveObj = TRUE,
                                 rescal.all.models = FALSE,
                                 do.full.models = FALSE,
                                 modeling.id='test')

     # 4. Evaluate model over another dataset (here the full one)

     ## creation of suitable dataset
     data <- cbind(GuloGulo=get_formal_data(myBiomodModelOut,'resp.var'), 
                   get_formal_data(myBiomodModelOut,'expl.var'))

     ## evaluation
     evaluate(myBiomodModelOut, data=data, stat=c('ROC','TSS'))

我遇到的问题是我无法从myResp和myBiomod_raster创建data.frame，因为# 4.1 Projection on current environemental conditions myBiomodProjection <- BIOMOD_Projection(modeling.output = myBiomodModelOut, new.env = myExpl, proj.name = 'current', selected.models = 'all', binary.meth = 'TSS', compress = FALSE, build.clamping.mask = FALSE) myBiomod_raster <- get_predictions(myBiomodProjection) #, as.data.frame=TRUE spp_occ <- myResp sauv_p <- as.vector(as.matrix(myBiomod_raster)) ROC_curve <- data.frame(result=sauv_p, spp=spp_occ) #préparation ROC_curve <- prediction(ROC_curve$result, ROC_curve$spp) #run AUC <- performance( ROC_curve, "auc" )@y.values print(AUC[[1]]) = 2488且myBiomod_raster的长度为5640。

错误是：参数意味着行数不同

您是否知道如何使用此Biomod2软件包示例中的数据来获得相同数量的行？

非常感谢！

来自Biomod2的ROCR的R AUC

0 个答案: