**4. Choice of machine learning (ML) model**

In the realm of data science, the choice of the appropriate machine learning model is critical in gaining the most information out of the data extracted while also being mindful of the computing resources needed to run the model (**Figure 3**).

*Developing and Deploying a Sepsis Deterioration Machine Learning Algorithm DOI: http://dx.doi.org/10.5772/intechopen.111557*


#### **Figure 3.**

*Rationale for selecting a machine learning algorithm.*

For the purposes of predicting sepsis deterioration, we will primarily be using regression to determine the association between variables (also known as features) to eventually predict an outcome variable of sepsis. As seen in our section above regarding validated sepsis scoring methodologies, all of our features are numerical making regression a reasonable choice for our model. The mathematics behind most forms of regression are complex but we will go through the basic premise of a few common types of regression.

