This is an initial exploratory exercise done for the class @ http://thiagomarzagao.com/teaching/ipea/ Text available here: https://arxiv.org/abs/1712.04429v1
The program:
Reads output from an ABM model and its parameters' configuration
Creates a socioeconomic optimal output based on two ABM results of the modelers choice
Organizes the data as X and Y matrices
Trains some Machine Learning algorithms
Generates random configuration of parameters based on the mean and standard deviation of the original parameters
Apply the trained ML algorithms to the set of randomly generated data
Outputs the mean and values for the actual data, the randomly generated data and the optimal and non-optimal cases
The original database from which the 232 samples of the actual data is read is large (60.7 GB) Thus, some pre-processed data for some pairs of optimal cases are also made available

This is a companion discussion topic for the original entry at https://www.comses.net/codebases/59d377e4-afa3-4937-a6fc-30cc50c1ac8f/releases/1.0.0/