Last updated: 2019-09-05

Checks: 7 0

Knit directory: polymeRID/

This reproducible R Markdown analysis was created with workflowr (version 1.4.0.9001). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.


Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

The command set.seed(20190729) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility. The version displayed above was the version of the Git repository at the time these results were generated.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:


Ignored files:
    Ignored:    .Rhistory
    Ignored:    .Rprofile
    Ignored:    .Rproj.user/
    Ignored:    analysis/library.bib
    Ignored:    docs/figure/
    Ignored:    fun/
    Ignored:    output/20190810_1538/
    Ignored:    output/20190810_1546/
    Ignored:    output/20190810_1609/
    Ignored:    output/20190813_1044/
    Ignored:    output/logs/
    Ignored:    output/natural/
    Ignored:    output/nnet/
    Ignored:    output/svm/
    Ignored:    output/testRunII/
    Ignored:    output/testRunIII/
    Ignored:    packrat/lib-R/
    Ignored:    packrat/lib-ext/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/BH/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/FactoMineR/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/IDPmisc/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/KernSmooth/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/MASS/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/Matrix/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/MatrixModels/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/ModelMetrics/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/R6/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/RColorBrewer/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/RCurl/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/Rcpp/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/RcppArmadillo/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/RcppEigen/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/RcppGSL/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/RcppZiggurat/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/Rfast/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/Rgtsvm/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/Rmisc/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/SQUAREM/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/SparseM/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/abind/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/askpass/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/assertthat/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/backports/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/base64enc/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/baseline/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/bit/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/bit64/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/bitops/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/boot/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/brew/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/callr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/car/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/carData/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/caret/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/cellranger/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/class/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/cli/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/clipr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/clisymbols/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/cluster/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/codetools/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/colorspace/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/commonmark/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/config/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/cowplot/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/crayon/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/crosstalk/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/curl/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/data.table/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/dendextend/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/desc/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/devtools/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/digest/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/doParallel/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/dplyr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/e1071/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/ellipse/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/ellipsis/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/evaluate/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/factoextra/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/fansi/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/flashClust/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/forcats/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/foreach/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/foreign/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/fs/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/generics/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/getPass/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/ggplot2/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/ggpubr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/ggrepel/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/ggsci/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/ggsignif/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/gh/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/git2r/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/glue/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/gower/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/gridExtra/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/gtable/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/haven/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/hexbin/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/highr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/hms/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/htmltools/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/htmlwidgets/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/httpuv/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/httr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/ini/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/ipred/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/iterators/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/jsonlite/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/keras/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/kerasR/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/knitr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/labeling/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/later/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/lattice/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/lava/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/lazyeval/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/leaps/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/lme4/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/lubridate/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/magrittr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/maptools/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/markdown/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/memoise/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/mgcv/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/mime/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/minqa/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/munsell/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/nlme/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/nloptr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/nnet/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/numDeriv/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/openssl/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/openxlsx/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/packrat/tests/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/pbkrtest/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/pillar/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/pkgbuild/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/pkgconfig/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/pkgload/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/plogr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/plotly/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/plyr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/polynom/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/praise/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/prettyunits/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/processx/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/prodlim/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/progress/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/promises/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/prospectr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/ps/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/purrr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/quantreg/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/randomForest/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/rcmdcheck/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/readr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/readxl/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/recipes/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/rematch/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/remotes/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/reshape2/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/reticulate/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/rio/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/rlang/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/rmarkdown/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/roxygen2/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/rpart/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/rprojroot/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/rsconnect/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/rstudioapi/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/scales/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/scatterplot3d/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/sessioninfo/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/shiny/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/sourcetools/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/sp/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/stringi/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/stringr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/survival/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/sys/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/tensorflow/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/testthat/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/tfruns/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/tibble/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/tidyr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/tidyselect/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/timeDate/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/tinytex/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/usethis/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/utf8/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/vctrs/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/viridis/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/viridisLite/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/whisker/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/withr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/workflowr/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/xfun/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/xml2/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/xopen/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/xtable/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/yaml/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/zeallot/
    Ignored:    packrat/lib/x86_64-pc-linux-gnu/3.6.1/zip/
    Ignored:    packrat/src/
    Ignored:    polymeRID.Rproj
    Ignored:    smp/20190812_1723_NNET/files/
    Ignored:    smp/20190812_1723_NNET/plots/
    Ignored:    smp/20190812_1729_NNET/files/
    Ignored:    smp/20190812_1729_NNET/plots/
    Ignored:    smp/20190812_1731_NNET/files/
    Ignored:    smp/20190812_1731_NNET/plots/
    Ignored:    smp/20190812_1733_NNET/files/
    Ignored:    smp/20190812_1733_NNET/plots/
    Ignored:    smp/20190815_1847_FUSION/
    Ignored:    smp/20190905_1602_FUSION/
    Ignored:    smp/20190905_1618_RFRAW/
    Ignored:    smp/20190905_1637_CNND2/
    Ignored:    smp/20190905_1708_FUSION/
    Ignored:    website/

Untracked files:
    Untracked:  analysis/elsevier-harvard.csl

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.


These are the previous versions of the R Markdown and HTML files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view them.

File Version Author Date Message
Rmd a848def goergen95 2019-09-05 changed citation style
html c26a428 goergen95 2019-08-22 Build site.
Rmd 7e9eddd goergen95 2019-08-22 wflow_publish(files = c(“analysis/cnn_crossvalidation.Rmd”, “analysis/cnn_exploration.Rmd”,
html f2ee83c goergen95 2019-08-19 Build site.
html 8c2286f goergen95 2019-08-19 added calibration.html
Rmd d960dc2 goergen95 2019-08-19 included calibration

Overview

For the calibration a decision fusion between the best performing models during the exploration stage was implemented. Since SVM-based models did not achieve very high accuracies we only included two RF models and two CNNs. The RF models yielding to the highest accuracies were trained with the raw data and the Savitzkiy-Golay smoothed data. For the CNNs we observed the highest accuracies with the second derivative of the raw data and with the second derivative of the normalized data. These models will be used during calibration. To gain an accuracy value for the fusion approach, again a cross-validation will be used.

Cross-Validation

The cross-validation of the decision fusion was conducted on ten folds and repeated five times. The complete code can be found here. For every fold, four models are trained and evaluated against a 50% test split. The final class decision is then achieved by combining the probability output of each model and assigning the class with the highest overall probability.

    classRFRaw = as.character(predict(rfModRaw, pcaRaw_testing))
    propRFRaw =  predict(rfModRaw, pcaRaw_testing, type = "prob")
    classRFSG = as.character(predict(rfModSG, pcaSG_testing))
    propRFSG = predict(rfModSG, pcaSG_testing, type = "prob")
    classCNND2 = as.character(classes[keras::predict_classes(cnnD2, x_testD2)+1])
    propCNND2 = keras::predict_proba(cnnD2, x_testD2)
    classCNNND2 = as.character(classes[keras::predict_classes(cnnND2, x_testND2)+1])
    propCNNND2 = keras::predict_proba(cnnND2, x_testND2)

    # probability
    probs = (propRFRaw + propRFSG + propCNND2 + propCNNND2) / 4
    pred = lapply(1:nrow(probs), function(x){
      which.max(probs[x,])
    })

    predVals = lapply(1:nrow(probs), function(x){
      probs[x,unlist(pred)[x]]
    })

    predVals = unlist(predVals)
    pred= names(unlist(pred))
    obsv = as.character(testingRaw$class)

    pred[which(pred %in% c("FIBRE","FUR","WOOD"))] = "OTHER"
    obsv[which(obsv %in% c("FIBRE","FUR","WOOD"))] = "OTHER"

    obsv = as.factor(obsv)
    pred = as.factor(pred)
    cfMat = caret::confusionMatrix(pred,obsv)

Note, that the classes which are not synthetic polymers are combined to a class called OTHER since we are only interested in the correct classification of plastic polymers. When a particle is correctly identified as non-plastic the main goal of the analysis is achieved, no matter if the different models disagree on the exact non-plastic class. By using the caret::confusionMatrix() function overall accuracy values are easily extracted as well as class specific metrics.

Results

By calculating the average across all folds and all repeats final accuracy results are obtained.

Tab. 1: Overall accuracy values for the decision fusion after cross-validation.
value
Accuracy 0.914
Kappa 0.894
AccuracyLower 0.824
AccuracyUpper 0.966
AccuracyNull 0.371

We achieved an overall accuracy of 91.4% with a Kappa coefficient of 0.89 (Tab. 1). This accuracy is substantially higher than compared to the single model accuracies of RF and CNN. By the decision fusion and combining the non-synthetic classes we were able to rise the accuracy by about 5%.

Tab. 2: Class-specific accuracy metrics for the decision fusion after cross-validation.
Sensitivity Specificity Pos Pred Value Neg Pred Value Precision Recall F1 Prevalence Detection Rate Detection Prevalence Balanced Accuracy
Class: HDPE 0.860 0.994 0.932 0.989 0.932 0.860 0.896 0.071 0.061 0.067 0.927
Class: LDPE 0.960 0.990 0.895 0.997 0.895 0.960 0.919 0.071 0.069 0.078 0.975
Class: OTHER 0.965 0.978 0.964 0.980 0.964 0.965 0.964 0.371 0.359 0.373 0.972
Class: PA 0.946 0.991 0.928 0.994 0.928 0.946 0.934 0.100 0.095 0.103 0.968
Class: PE 0.895 0.996 0.948 0.994 0.948 0.895 0.912 0.057 0.051 0.055 0.946
Class: PES 0.691 0.980 0.832 0.967 0.832 0.691 0.734 0.100 0.069 0.087 0.836
Class: PET 0.755 0.974 0.658 0.985 0.658 0.755 0.688 0.057 0.043 0.067 0.865
Class: PP 1.000 0.999 0.989 1.000 0.989 1.000 0.994 0.086 0.086 0.087 0.999
Class: PS 0.987 0.999 0.980 0.999 0.980 0.987 0.981 0.043 0.042 0.043 0.993
Class: PUR 0.920 0.999 0.978 0.997 0.978 0.920 0.960 0.043 0.039 0.041 0.959

Analyzing the class-specific accuracy metrics (Tab. 2) we observe that the lowest sensitivity is 0.69 for PES. That means that PES is most likely not to be identified correctly. PET shows a similar low sensitivity value of 0.76. PP shows the highest sensitivity value of 1, which means that all samples classified as PP actually represent that class. Concerning the specificity, gor all classes similar values of about 0.99 are observed. In general, it can stated that a very good distinction between non-synthetic polymers and microplastic polymers was achieved. However, some microplastic classes, such as PES and PET achieve only poor accuracies (0.84 and 0.86 of balanced accuracy respectively). These shortcomings might be compensated for with extensions to the reference database. Machine learning algorithms can only learn from the database which is presented to them. Therefore, adding reference samples could prove beneficial when it comes to accuracy.


sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Linux Mint 19.1

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.7.1
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.7.1

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=de_DE.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=de_DE.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] tensorflow_1.14.0         abind_1.4-5              
 [3] e1071_1.7-2               keras_2.2.4.1            
 [5] workflowr_1.4.0.9001      baseline_1.2-1           
 [7] gridExtra_2.3             stringr_1.4.0            
 [9] prospectr_0.1.3           RcppArmadillo_0.9.600.4.0
[11] openxlsx_4.1.0.1          magrittr_1.5             
[13] ggplot2_3.2.0             reshape2_1.4.3           
[15] dplyr_0.8.3              

loaded via a namespace (and not attached):
 [1] reticulate_1.13  tidyselect_0.2.5 xfun_0.8         purrr_0.3.2     
 [5] lattice_0.20-38  colorspace_1.4-1 generics_0.0.2   htmltools_0.3.6 
 [9] yaml_2.2.0       base64enc_0.1-3  rlang_0.4.0      pillar_1.4.2    
[13] glue_1.3.1       withr_2.1.2      foreach_1.4.7    plyr_1.8.4      
[17] munsell_0.5.0    gtable_0.3.0     zip_2.0.3        codetools_0.2-16
[21] evaluate_0.14    knitr_1.24       SparseM_1.77     tfruns_1.4      
[25] class_7.3-15     highr_0.8        Rcpp_1.0.2       scales_1.0.0    
[29] backports_1.1.4  jsonlite_1.6     fs_1.3.1         digest_0.6.20   
[33] stringi_1.4.3    grid_3.6.1       rprojroot_1.3-2  tools_3.6.1     
[37] lazyeval_0.2.2   tibble_2.1.3     crayon_1.3.4     whisker_0.3-2   
[41] pkgconfig_2.0.2  zeallot_0.1.0    Matrix_1.2-17    assertthat_0.2.1
[45] rmarkdown_1.14   iterators_1.0.12 R6_2.4.0         git2r_0.26.1    
[49] compiler_3.6.1