For machine learning, we need systems that can process nonlinear and unrelated sets of data. This is very important so that we can make predictions for bankruptcy problems, since the relationship between the default and explanatory variables will rarely be linear. Therefore, using neural networks is the best possible solution.
Artificial neural networks (ANNs) have long since been used to solve bankruptcy problems. An ANN is a computer system that has a number of interconnected processors. These processors provide outputs by processing information and by responding dynamically to the inputs that are provided. A prominent and basic example of ANN is the multilayer perceptron (MLP). An MLP can be represented as follows:
Except for the input nodes, each node is a neuron that uses a nonlinear activation function, which was sent in.
As is evident from...
