More observations,
I have noticed that supposedly identical nets will train differently and produce different results under certain situations.
Nets that are set up with individual inputs that have multiple boxes checkmarked will train differently than the same identical net that has an individual input for each box checked. I do not know which is better for certain, but I am leaning towards one box checked for each input. Setting up nets this way may, of course, be a problem for people using shareware versions that are limited to seven inputs.
Nets that are trained using the maximum available neurons from the start or near to the start of training, train differently than those trained by starting with a minimal amount and letting the program add more neurons as needed. Nets trained by adding more as you go seem to be more finely tuned, especially if you have both back prop and annealing checked. I attribute this to the fact that every time the net adds more neurons it trains through an entire cycle of back prop and all four phases of annealing. And as a result of going through all of the annealing training passes each time new neurons are added, nets trained this way take quite a bit longer to train. Which is better? I am leaning towards starting with 6 to 14 and letting the net add more as it goes.
One final observation: Not all, but most of the premature buy signals can be eliminated by using the Skittish strategy, which only buys when sure and sells at the first sign of a possible downtrend. Nets that I have trained from the beginning using this strategy rarely produce premature buy signals in the verify period.
There is an old saying about how to make money in the market, that being, never buy at the bottom and always sell too soon. If anyone has any methods for setting up nets that will produce buy and sell signals that will conform to the trading strategy of this saying, please post the settings.
Jay |
