# selecting test data for neural networks

I have been working on a neural network based on certain technical indicators. As people familiar with neural networks would know after developing a hypothesis, the developer is also supposed to provide a set of data to learn from. Now if were a case of developing neural networks for spam fitering I would provided it with sets of spam and non spam data. But in my case how do I select the buy/sell point...do I just randomly select the entry points where can visually see the movement in price that I desire or is there a better approach?

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I've been thinking about your question and wanted to ask for some clarification. Sorry if this sounds daft, but does your NN output buy/sell signals based on time relevant values of TAs? Or are you trying to forecast something? –  Armen Safieh-Garabedian Dec 18 '13 at 15:39

If $price_{t+interval} > price_t$ + transaction costs then position = 1.