Users indeed sometimes want to see how financial issues are inter-related, like for instance patterns on Intel, then tested on Dell. You may be surprised to see how patterns can be correlated. Genetic algorithms are optimizers, i.e do not 'learn'. A number of users have chosen not to do OoS analysis at all. This may sound obvious but do not use the G.P.F. on securities that have been plain bullish over the whole period of your data series.
Successful trading is meant to beat a 'buy and hold' strategy.
If you wish to optimize for the best 'Average Size' signal, you may want to use the outlier filtering which indeed may distort the average return. Yet, in most cases, trading is all a matter of taking advantage of the 'fat-tailed' return distribution particular to stocks. Like most professional traders, we feel it would be defeating the point. The G.P.F. will find the best patterns for the provided specifications, unless you use early stopping techniques that are too constraining. But this does not mean that there are winning patterns for all stocks.