Cross-Validation for Predictive Analytics Using R - MilanoR

Since ancient times, humankind has always avidly sought a way to predict the future. One of the most widely known examples of this kind of activity in the past is the Oracle of Delphi, who dispensed previews of the future to her petitioners in the form of divine inspired prophecies1. In the modern days, the desire to know the future is still of interest to many of us, even if my feeling is that the increasing rapidity of technology innovations we observe everyday has somewhat lessened this instinct: things that few years ago seemed futuristic are now available to the great mass (e.g. the World Wide Web). Among the many areas of the human being where predictions are highly needed there is business decision making. The tools for formulating predictions about quantities of interest are commonly known as predictive analytics, which is itself an essential part of data science.