This final chapter has served us to revise the concepts learned in previous chapters; this time, without any introductions, but starting with a real-life case and analyzing the workflow that allows us to extract knowledge from a database.
In this chapter, we started with solving a fitting problem. We created a model that allows us to calculate the concrete compressive strength according to the ingredients used in the mixture. We learned how to import data in the MATLAB workspace and how to prepare it for subsequent analysis. Then, we resolved a fitting problem using Neural Network Toolbox.
Then, we learned how to use neural network to classify pattern. In this study, we created a model that allows us to classify thyroid diseases according to a lot of patient data. This time, we used a dataset that was already available in the MATLAB distribution. We also learned to build and understand the confusion matrices and the ROC.
Finally, we performed a clustering analysis. The purpose of this...