Multi Expression Programming X

Genetics has been one of the main beneficiaries of the digital revolution, as mathematically complex analyses could now be conducted without the need of laborious pen and paper operations. Given the sheer number of components involved in any modern scientific foray, statistical methods have found a very good application in this domain and Multi Expression Programming X seeks to further this trend by providing its users with the ability of applying genetic programming algorithms to solve complex issues.

Uses single or multiple mathematical operators to perform data analyses

As with any data analyzer, the program requires valid input information, and this can be imported from either CSV or TXT documents. Once figures have been loaded, users can employ single or multiple mathematical operators on either regression or two-class classification problems.
Among the valid operators, one can mention all the trigonometric functions, additions, subtractions, but also minimum and maximum criteria. Users also have complete control over the subpopulations used, as well as the effective size per each item.

Makes use of multiple CPU cores

Crossover probabilities can be defined and the application is compatible with both uniform and one-cutting point crossover types. Scientists can employ either automatically generated constants or user-defined ones and the number of simulations performed by the program can also be controlled.
It should be noted that the mathematical algorithms employed are quite complex and the higher the number of runs is set to, the longer the analysis will take. The program supports multithreading operations and all analysis results are dumped in a tabular layout for easy access to data; source C code is also created based on the input parameters and simple CSV containers can be employed to export the results.

An overall comprehensive data analysis program based on evolutionary algorithms

To conclude, Multi Expression Programming X is a great tool for scientists wishing to apply the Multi Expression Programming algorithms to their chosen genetic research. The program allows multiple adjustments to the input parameters, including concerning the mathematical operators used.