Now that we have learned how to develop a powerful model to predict bank failures, we will test a final option to develop different models. Specifically, we will try out automatic machine learning (autoML), which is included in the h2o package. The process that we have carried out to build many models and find the best one without any prior knowledge is done automatically by the autoML function. This function trains different models by trying different grids of parameters. Moreover, stacked ensembles or models based on previously trained models are trained to find more accurate or predictive models.
In my opinion, using this function before launching any model is highly recommended to get an initial idea of a reference starting point. Using an automatic approach, we can assess the most reliable algorithms, the most important potential variables to be...
