The Nine-step process in conducting a neural network project.docx - In step one the data to be utilized for training and testing the network are

The Nine-step process in conducting a neural network project.docx

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In step one, the data to be utilized for training and testing the network are gathered. Important considerations are that the particular problem is amenable to neural network arrangement and that adequate data exist and can be obtained ( Omar, 2016) . In step two, training data must be recognized, and a plan must be made for testing the performance of the network. The third and fourth step involves the selection of network architecture and a learning method. In these steps, the neural network design is developed. It includes topology selection and determination of input and output nodes, hidden layers, and hidden nodes quantity. The input nodes must be based on the data sets available. According to Turban et al. (2014), after choosing the NN structure, a learning algorithm is identified. This is to identify connection weight sets that are best in covering data training as well as having better predictive accuracy ( Turban, 2016) .

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