News archive for December 2011

DataModeler Release 8.05 (7 December)

Thursday, December 8, 2011

The theme for this release is improved (and beautiful) model analysis. We have another suite of functions in development targeted at VariableContributionAnalysis; however, rather than hold things up while that gets lined out, we decided to get this out the door since the changes since the multi-core release are fairly extensive as well as practically useful. Since the variable contribution analysis tools are in the pipeline, the QuickStart, case studies and function examples have not yet been refreshed to illustrate these new tools. That will be part of the next release.

The theme for this release is model analysis. We have another suite of functions in development targeted at VariableContributionAnalysis; however, rather than hold things up while that gets lined out, we decided to get this out the door since the changes since the multi-core release are fairly extensive as well as practically useful. Since the variable contribution analysis tools are in the pipeline, the QuickStart, case studies and function examples have not yet been refreshed to illustrate these new tools. That will be part of the next release.

The release notes are below. Other than working around a Mathematica bug that makes the normal way of suppressing warning messages from SymbolicRegression via Quiet impossible, we have some important new functionality which is pretty slick:

  • ModelDimensionalityTable: This lets us look at the number of variables required for models. This is especially nice when we have coupled inputs so that different variable combinations can achieve quality models. This function also makes extensive use of tooltips to maximize the information content and accessibility.
  • VariablePresenceChart: This provides a quick visual of the relative presence of model variables. It is related to the VariablePresenceMap as well as the VariableCombinationChart. In addition to also using tooltips to provide additional content, it is a smart function in that, for example, changing the BarOrigin will make intelligent adaptations in option settings.
  • CorrelationChart: This provides a 1-D slice of the CorrelationMatrixPlot and is useful for getting a quick overview of the linear relationships between inputs and targeted response. Of course, this function also features tooltips as well as intelligent adaptation of option settings.
  • VariablePresenceDistributionChart: During modeling we want to run multiple IndependentEvolutions (which are facilitated by the multi-core support of current generation CPUs). Since each model search follows a different path, it is useful to look at the variability between these different searches since there can be multiple paths to achieving high-quality models. Towards that end, this release features model tagging and functions to allow separating the IndependentEvolutions. In this function we can see some of the variable substitutions which are possible and identify inputs which may merit further investigation despite not rising to the forefront within an aggregated analysis. Consistent with the theme of this release, these functions have intelligent option setting adaptation as well as tooltips to maximize the information transfer.

Of course, all of the new functions can handle data with missing or non-numeric elements and have lots of flexibility in terms of their usage and inputs.

Enjoy!