Clustering refers to grouping of similar records [3]. This is
used as a preprocessing stage before the data is added into
classifying model. The values should be normalized before
clustering by avoiding the domination of high value attribute to
low value attributes. Neural Network (NN) is a collection of
neurons interconnected between two or more network layers
implemented in various diseases prediction used in paper [2, 4].
It is made up of three layers input layer, hidden layer and output
layer. It uses linear transfer function as input layer and non
linear transfer function as output layer. In the first stage it sets
transfer function and network parameters and calculates output
of every neuron in hidden layer and estimates output in hidden
layer.