how to

• Rscript run_classifiers.R runs all the defined classifiers (in methods.R) over all datasets (by default now only on the fast binary datasets). You can pass optional arguments, in that case the format is:

  Rscript run_classifier.R DATA CLASS1 CLASS2 CLASS3 ... 
  

  where DATA can be the name of one of the datasets (e.g. Asym) or the name of a tsv file containing a list of datasets (e.g. binary_fast_datasets_names.tsv). The arguments CLASS1 CLASS2 ...
  are identifiers of classifiers: the name of a method (e.g. bnc_nb for the naive bayes implemented in bnclassify) or the name of a family of methods such as bnc_ in that case all classifiers in the bnc_ family will be executed (the final _ is important!)

  examples :

  • run all methods in the st_ family (stagedtrees) and the simple classifier over the Titanic dataset:

  Rscript run_classifiers.R Titanic st_ simple 
  

  • run the simple classifier over all the datasets:

  Rscript run_classifiers.R datasets_names.tsv simple 
  

• Running aggregate.R the available results will be evaluated according to the measures defined in statistics.R and saved in a multidimensional array TABLE.rds. Values for plotting roc curves are saved into the multidimensional array ROC_CURVES.rds.

• The script plot.R takes the aggregated tables TABLE.rds and ROC_CURVES.rds and produces plots.

See the available methods in METHODS.md and the available datasets in datasets_names.tsv.

order experiments

• Rscript run_order.R DATA st_naive_order st_fbhc_order

• Rscript aggregate_order.R DATA

• Rscript plot_order.R DATA

where DATA is the name of one of the datasets.