When implementing a PDT run, various analytics are generated at the end of each generation. Below we give a brief description of each of the graphs available on the Analytics tab (visible only after a run has been started).
The responses for each generation are sorted, and presented one after the other. Standard error bars are given at the top of each colored bar.
Detail of the previous graph, giving a separate graph of sorted responses for each generation.
A summary of the data in the previous two graphs, sorted response barplots for each generation overlapping each other, in different colors.
A boxplot representation of the distribution of response values, generation by generation.
The response of all responses in all generations.
Response histograms, generation by generation.
For each experimental parameter (i.e., each of the variables specified in the experimental space definition), the relative representation of that parameter is represented for each generation. Relative representation is measured by a percentage, namely the percentage of experiments for a given generation having a particular parameter at a particular value.
In the course of evolution, parameter values that have low representation tend to be those that do not contribute to high response; those with high representation tend to contribute more.
This plot uses the R package CTree. CTree is a non-parametric class of regression trees embedding tree-structured regression models into a well defined theory of conditional inference procedures.
For data sets with relatively simple structure, this tree will have only a few nodes. (NB: this may be the case with the synthetic data in the demo runs.)