Function reference

Experimental Data Manipulation

This functions manipulate the experiment objects, implementing common data manipulation operations, such as subseting and joining. In addition, there are a number of available functions to sanitize and preprecessing the experimental data such as looking for duplicated entries, reducing parameters and instantiating the methods with the parameters.

  • expCreate
    Load data and create an exreport experiment
  • expCreateFromTable
    Create an exreport experiment from a tabular representation
  • expCombine
    Combine two experiments with different outputs
  • expConcat
    Concatenate rows of matching experiments
  • expExtend
    Extend an experiment by adding new parameters
  • expExtract
    Extract statistically equivalent methods from a multiple comparison test
  • expGetDuplicated
    Create a new experiment with only the duplicated rows
  • expInstantiate
    Instatiate the methods in the experiment for each one of the different parameter configurations.
  • expReduce
    Reduce a parameter by a function for each method, problem and remaining parameter configuration interaction
  • expRemoveDuplicated
    Remove duplicated rows from an experiment
  • expRename
    Change the name of elements that an experiment contains
  • expReorder
    Change the order of elements that an experiment contains
  • expSubset
    Obtains a subset of an experiment matching the given conditions

Statistical Tests

This functions implement several statistical test to compare the methods of the experiment.

Tabular Data Generation

This functions generate tables summarizing the information of an experiment or a text to be printed to pdf or web reports.

Graphical Plots

This functions generate plots summarizing the information of an experiment or a text to be printed to pdf or web reports.

Rendering Reports

These are the main functions used to generate and render the reports


Example problems for the examples and documentations

  • wekaExperiment
    Problem: Comparison between several Machine Learning algorithms from the Weka library