Add a method to validate result produced by workers

[gmontamat]

The distributed version of the algorithm receives results from the workers without validating their work. This is safe when one has control of all the instances running the worker nodes but it is dangerous when one shares the queue of jobs on the internet.
When opening the genetic algorithm to the world, a malicious user may return a fake metric claiming to have trained the model using k-fold cross validation, corrupting the overall result of the parameter tuning.
Some options to prevent this from happening are to:

• Send the workers a random dev set after they finish evaluating an individual and ask them to make predictions using the model trained
• Use different workers at random to evaluate the same individual and cross-check their results
• Find a proof of work like the time it used to run, maybe ask for partial results
• Blockchain? (j/k, no way!)

[gmontamat]

Another approach is to:
Generate a docker image for the clients (aka workers) code with obfuscated code and encrypted server credentials so that anyone running it cannot modify the code.