So far, we have been working with supervised learning for predicting numerical values; however, in the real world, numbers are just part of the data addressed. Real variables also contain categorical values, which are not purely numerical, but describe important features that have influence on the problems neural networks are applied to solve. In this chapter, the reader will be presented with a very didactic but interesting application involving categorical values and classification: disease diagnosis. This chapter digs deeper into classification problems and how to represent categorical data, as well as showing how to design a classification algorithm using neural networks. The topics covered in this chapter are as follows:
Foundations of classification problems
Categorical data
Logistic regression
Confusion matrix
Sensibility and specificity
Neural networks for classification
Disease diagnosis using neural networks
Diagnosis for cancer
Diagnosis for diabetes...