Input Selection – In this mode the genetic algorithm selects which of the inputs you have chosen are most useful. Only the ones it decides are best are used in the final training. Note that the usefulness of an input is evaluated in conjunction with all other inputs. In other words, the GA is really finding an optimum SET of inputs, not inputs that are necessarily useful by their self. These inputs do not have to be indicators built by the Trader. They can be any data stream you load. You can add quite a few more indicators than you want to eventually use (we wouldn’t suggest many more than 20 to 60 for best results). Elsewhere in the wizard you will specify the maximum number of inputs that you want the GA to keep (we like between 3 and 12 to enhance chances of good generalization). The GA will search through combinations looking for the set of inputs which is less than or equal to the maximum number of inputs that you specified and which, as a set during training, optimizes the training criteria (e.g., maximize profit, minimize error, etc.). No parameters of any of the inputs that are indicators are modified or optimized; they are used just as you have specified them.
Parameter Search – In this mode, the genetic algorithm will use all of the inputs you have chosen, but it will optimize the parameters of all indicators you have used as inputs, even if they are embedded in other indicators. In other words, if one of your inputs is the 10 period lag of the 5 period momentum of the close, the genetic algorithm may change the periods to 6 and 3 respectively if the resulting indicator works best. (You can even tell it to select among open, high, low, and close). Note that the evaluation is in combination with the other optimized indicators and other inputs. In other words, it is possible that the parameterization of an indicator does not produce an indicator that is useful by itself. It may only be useful in combination with the entire set of optimized inputs. Note that optimization can only be accomplished on indicators which you have entered using the NeuroShell Trader’s Indicator Wizard (even if it was entered from the Prediction Wizard). Other data streams used as inputs will still be used during optimization, but not optimized. Keep your number of inputs between 5 and 30 for best results.
Full Optimization – In this mode, both Input Selection and Parameter Optimization are accomplished at the same time. This is a very advanced concept, and we are not currently aware of any other programs capable of this using a GA. Note however, that the GA is doing more work (i.e., using more variables) than in doing either input selection or parameter optimization separately. Therefore, for best results, keep your number of inputs below about 30 if they are all indicators.
No Optimization – In this mode, neither Input Selection nor Parameter Optimization is used. The inputs are used just as you have selected them.
There is an additional form of optimization called threshold optimization that can take place (or not) in any of the modes above, including the no optimization mode. Threshold optimization is discussed in Prediction Parameters – Positions and Neural Network Network Parameters Discussion (Objective).
Topics of Interest:
What are Neural Networks?
What are Genetic Algorithms?
How Does a Genetic Algorithm Work?
Why is a Genetic Algorithm Better Than Other Optimizers?
What Types of Problems Do Genetic Algorithms Solve?
How are Genetic Algorithms Used in the NeuroShell Trader Professional?