This chapter will provide you with an overview of the random forest algorithm. We will first look at the decision tree algorithm and, once we have a handle on it, try to understand the random forest algorithm. Then, we will use Core ML to create a machine learning program that leverages the random forest algorithm and predicts the possibility of a patient being diagnosed with breast cancer based on a given set of breast cancer patient data.
As we already saw in Chapter 1, Introduction to Machine Learning on Mobile, any machine learning program has four phases: define the machine learning problem, prepare the data, build/rebuild/test the model, and deploy it for usage. In this chapter, we will try to relate these with random forest and solve the underlying machine learning problem.
Problem definition: The breast cancer data for certain patients is...
