What types of neural networks are used in TradingSolutions?
A. TradingSolutions comes with several general neural network models that you can use to develop predictions. By default, the program automatically selects an appropriate pre-configured model for the prediction being made. In most cases, beginning and intermediate users can simply continue from this panel without changing any options. However, there may be times when you want to select a different model, modify the pre-configured model, or specify to use a subset of the data for training. The neural network models in TradingSolutions are broken into two basic types: static neural networks and dynamic neural networks. Static neural networks train and predict using only current input information. This makes them good for classification problems in that they treat each set of inputs as a separate case. Static networks can also be used for time-series predictions by providing multiple historical samples as inputs. Static neural networks include multilayer perceptrons (MLP), modular network
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