Python for Finance Cookbook

Getting ready

In this recipe, we build on top of what we already established in the Implementing scikit-learn's pipelines recipe from the previous chapter, where we created the default prediction pipeline, from loading the data to training the classifier. We use the variant without the outlier removal procedure (introduced in the There's more... section of that recipe). In this recipe, we will be replacing the last step (the estimator) with different, more advanced ones. Additionally, we fit the decision tree pipeline to the data to obtain the baseline model for performance comparison. For your convenience, we reiterate all the required steps in the Notebook accompanying this chapter.