There are many different neural network models that have been developed over the last fifty years or so to achieve these tasks of prediction, classification, and clustering.
4CastXpress model a multilayered feedforward neural network (MFNN) and is an example of a neural network trained with supervised learning.
We feed the neural network with the training data that contains complete information about the characteristics of the data and the observable outcomes in a supervised learning method. Models can be developed that learn the relationship between these characteristics (inputs) and outcomes (outputs).
For example, we can develop a MFNN to model the relationship between money spent during last week’s advertising campaign and this week’s sales figures is a prediction application.
Another example of using the holy grail forex trading system a MFNN is to model and classify the relationship between a customer’s demographic characteristics and their status as a high-value or low-value customer. For both of these example applications, the training data must contain numeric information on both the inputs and the outputs in order for the MFNN to generate a model.
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