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Management Support Systems
Notes system or as part of another software system where new input data will be presented to it and its
output will be a recommended decision. In the following sections, we examine these steps in
more detail.
Figure 11.9: Flow Diagram of the Development Process of an ANN
Source: http://www70.homepage.villanova.edu/matthew.liberatore/Mgt2206/turban_online_ch06.pdf
11.2.1 Data Collection and Preparation
The first two steps in the ANN development process involve collecting data and separating
them into a training set and a testing set. The training cases are used to adjust the weights, and
the testing cases are used for network validation. The data used for training and testing must
include all the attributes that are useful for solving the problem. The system can only learn as
much as the data can tell.
Did u know? Collection and preparation of data is the most critical step in building a good
system.
11.2.2 Selection of Network Structure
After the training and testing data sets are identified, the next step is to design the structure of
the neural networks. This includes the selection of a topology and determination of
input nodes,
output nodes,
number of hidden layers, and
number of hidden nodes.
The multilayer feedforward topology is often used in business applications, although other
network models are beginning to find some business use as well.
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