Version 0.6.0 on CRAN

• Extensive tests on Intermediate Concepts, which are also integrated into the
  new README.Rmd file (and README) as well as in test scripts TestCases.R and
  TestCases_NoObject.R on Github.
• Fixed inverted axis bug in plot in plot.ciu.3D.
• Integrated support for mlr3. Only tested with "classif.rpart" model though
  because other tested models (xgboost, nnet, ...) don't like R types and no
  need/time to dive into mlr3 for the moment. To fix in the future in case bugs
  are discovered.
• Added parameter "plot.mode" to "ciu.ggplot.col" function, which allows for value
  "overlap" that plots CI as a bar and then CU as another bar over it, scaled
  into CI bar. Colour of CU bar can either be fixed (dark green by default) or set to NULL,
  which then uses the green-yellow-red color scale (unless those colours are
  changed by the function parameters).
• Removed parameter for min/max values of contextual influence because the
  range of contextual influence is (and should be) always one (1) based on
  the mathematical constructs.
• Added new method "ggplot.ciu" to ciu.new for plotting input/output graphs with
  ggplot. Identical to old plot.ciu, except that 1) ggplot offers some
  advantages, notably what comes to figure scaling, 2) added possibility to
  include CIU visualisation (cmin, cmax, neutral) by setting "illustrate.CIU=TRUE".
• Added new method "influence" to ciu.new for getting numerical contextual
  influence (rather than just seeing them in plots).
  TO-DO: add corresponding function to "ciu.R".
• Corrected axis in plot.ciu.3D.

CRAN Release v0.5.0

This is a major update compared to the previous release (v0.1.0).

• Textual explanations have been implemented with function "ciu.textual".
• Implemented "meta.explain" method, which returns a self-contained
  "ciu.meta.result" object with CIU results for a given instance.
  This mainly makes it possible to visualize exactly the same CIU result
  in different ways.
  Before this (and still if no "ciu.meta" parameter is given), every
  visualization method ran "explain" again, so CIU results could differ
  somewhat between different runs.
• Added parameters "use.influence" and "influence.minmax" to "ggplot.col"
  and "barplot.ciu" functions/methods, which produces a LIME/SHAP/etc-like plot
  where "influence = (influence.max - influence.min)*ci(cu-neutral.CU)", bars
  go either right or left of zero and there are only two colours.
• Added support for factor-type inputs to method "$plot.ciu".
• Created new "class" called "ciu", which is just a list object with the
  "instance variables" of a CIU object. This makes it possible to create
  plot functions that are not methods of CIU but rather take a "ciu" object
  as their first parameter. The main reason for doing this modification is that
  CIU objects seem to use much more memory than a simple data-based "ciu" object.
  The documentation and package tools in R are also not too aware about
  "inner functions" (methods), which is an inconvenient. Finally, the plan was
  indeed to go for this approach in any case because increasing the code length
  of CIU was not desirable in the long run. The way in which it is implemented
  now allows functions and methods to be used interchangeably in any case.

First version published at CRAN

This is the first version of the Contextual Importance and Utility (ciu) package published at CRAN. It is well-tested with a limited number of users but some needs for patches might turn up when it is used in new contexts.