Methods for a holistic view
As discussed in the previous section, in this section, we need to select our analytical methods or models (equations) to complete the task of mapping our business use case to machine learning methods.
To assess the impact of various factors on the sales team's success, there are many suitable models for us to use. As an exercise, we will select (a) regression models, (b) structural equation models, and (c) decision trees, mainly for their ease of interpretation as well as their implementablility on Spark.
Once we finalize our decision for analytical methods or models, we will need to prepare the dependent variable and also prepare for coding; we will discuss these one by one in the following section.
Regression modeling
To get ready for regression modeling on Spark, there are three issues for us to take care of:
Linear regression or logistic regression.
Regression is the most mature and also the most widely used model to represent the impact of various factors on one...
