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topepo / caret

caret (Classification And Regression Training) R package that contains misc functions for training and plotting classification and regression models
http://topepo.github.io/caret/index.html
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predict.plsda fails using example code #1119

Open vjcitn opened 4 years ago

vjcitn commented 4 years ago

the example for plsda is blocked with \dontrun

but if you copy the code into a session 

data(mdrr)
     set.seed(1)
     inTrain <- sample(seq(along = mdrrClass), 450)

     nzv <- nearZeroVar(mdrrDescr)
     filteredDescr <- mdrrDescr[, -nzv]

     training <- filteredDescr[inTrain,]
     test <- filteredDescr[-inTrain,]
     trainMDRR <- mdrrClass[inTrain]
     testMDRR <- mdrrClass[-inTrain]

     preProcValues <- preProcess(training)

     trainDescr <- predict(preProcValues, training)
     testDescr <- predict(preProcValues, test)

     useBayes   <- plsda(trainDescr, trainMDRR, ncomp = 5,
                         probMethod = "Bayes")
     useSoftmax <- plsda(trainDescr, trainMDRR, ncomp = 5)

then the next line is

>      confusionMatrix(predict(useBayes, testDescr),
+                      testMDRR)
Error in predict.NaiveBayes(object$probModel[[ncomp[i]]], as.data.frame(tmpPred[,  : 
  Not all variable names used in object found in newdata
> sessionInfo()
R Under development (unstable) (2020-02-08 r77784)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Mojave 10.14.6

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] caret_6.0-85    ggplot2_3.2.1   lattice_0.20-38 rmarkdown_2.1  

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.3           lubridate_1.7.4      class_7.3-15        
 [4] assertthat_0.2.1     digest_0.6.23        ipred_0.9-9         
 [7] foreach_1.4.8        mime_0.9             R6_2.4.1            
[10] plyr_1.8.5           stats4_4.0.0         evaluate_0.14       
[13] highr_0.8            pillar_1.4.3         rlang_0.4.4         
[16] lazyeval_0.2.2       rstudioapi_0.11      data.table_1.12.8   
[19] miniUI_0.1.1.1       rpart_4.1-15         Matrix_1.2-18       
[22] combinat_0.0-8       startup_0.14.0       splines_4.0.0       
[25] gower_0.2.1          stringr_1.4.0        questionr_0.7.0     
[28] munsell_0.5.0        shiny_1.4.0          compiler_4.0.0      
[31] httpuv_1.5.2         xfun_0.12            pkgconfig_2.0.3     
[34] htmltools_0.4.0      nnet_7.3-12          tidyselect_1.0.0    
[37] tibble_2.1.3         prodlim_2019.11.13   codetools_0.2-16    
[40] crayon_1.3.4         dplyr_0.8.4          withr_2.1.2         
[43] later_1.0.0          MASS_7.3-51.5        recipes_0.1.9       
[46] ModelMetrics_1.2.2.1 grid_4.0.0           nlme_3.1-143        
[49] xtable_1.8-4         gtable_0.3.0         lifecycle_0.1.0     
[52] magrittr_1.5         pROC_1.16.1          scales_1.1.0        
[55] stringi_1.4.5        reshape2_1.4.3       promises_1.1.0      
[58] timeDate_3043.102    pls_2.7-2            generics_0.0.2      
[61] lava_1.6.6           klaR_0.6-15          iterators_1.0.12    
[64] tools_4.0.0          glue_1.3.1           purrr_0.3.3         
[67] fastmap_1.0.1        survival_3.1-8       colorspace_1.4-1    
[70] knitr_1.28
Evelyn3333 commented 6 months ago

same problem, looking for some help.