Welcome to Vegetto’s documentation!¶
Vegetto is a DEAP-based evolutionary procedure designed to solve multi-objective optimization feature selection problems.
Specifically, a wrapper has been designed where NSGA-II is used as search strategy, while k-NN is used as classification algorithm for the evaluation of potential solutions.
This wrapper is designed with two premises in mind: to reach solutions as close as possible to the global optimum and to perform the computation in an efficient way. For the latter, four efficient versions of k-NN have been developed in C++, where the data conversion between both languages is carried out with the Pybind11 library. If maximum efficiency is desired, the last version of k-NN should be chosen, since this is a mechanism that chooses the most optimal version depending on the number of selected features.