Machine Learning for Healthcare Analytics Projects

Training models 

Now, let's move on to actually defining the training models:

1. First, make an empty list, in which we will append the KNN model.
2. Enter the KNeighborsClassifier function and explore the number of neighbors.
3. Start with n_neighbors = 5, and play around with the variable a little, to see how it changes our results.

4. Next, we will add our models: the SVM and the SVC. We will evaluate each model, in turn.
5. The next step will be to get a results list and a names list, so that we can print out some of the information at the end.
6. We will then perform a for loop for each of the models defined previously, such as name or model in models. 
7. We will also do a k-fold comparison, which will run each of these a couple of times, and then take ...