Genetic algorithms are used to solve many optimization tasks.
If I have a dataset, can I evolve it with a genetic algorithm to create an evolved version of the same dataset?
We could consider each feature of the initial dataset as a chromosome (or individual), which is then combined with other chromosomes (features) to find more features. Is this possible? Has this been done?
I will like to edit the details with an example so that it is easier to understand.
Example: In practice cyber-security attacks evolve over time since it finds a new way to breach a system. The main draw-back of intrusion detection model is that it needs to be trained every time attack evolves. So I was hoping if genetic algorithm can be used on the present benchmarked datasets (like NSL-KDD) to come up with a futuristic type dataset maybe after X-number of generations. And check if a model is able to classify that generated dataset as well.