Training the machine learning model

The goal is to select the most appropriate algorithm for building the machine learning model, training it, and then analyzing the results received. We begin by selecting appropriate machine learning techniques to analyze the data. The next chapter, that is, Chapter 2, Random Forest on iOS, will talk about the different machine learning algorithms and presents details of the types of problems for which they would be apt.

The training process and analyzing the results also varies based on the algorithms selected for training.

The training phase usually uses all the attributes of data present in the transformed data, which will include the predictor attributes as well as the objective attributes. All the data features are used in the training phase.