Example – estimating the quality of wines with regression trees and model trees

Winemaking is a challenging and competitive business that offers the potential for great profit. However, there are numerous factors that contribute to the profitability of a winery. As an agricultural product, variables as diverse as the weather and the growing environment impact the quality of a varietal. The bottling and manufacturing can also affect the flavor for better or worse. Even the way the product is marketed, from the bottle design to the price point, can affect the customer's perception of taste.

As a consequence, the winemaking industry has heavily invested in data collection and machine learning methods that may assist with the decision science of winemaking. For example, machine learning has been used to discover key differences in the chemical composition of wines from different regions, or to identify the chemical factors that lead a wine to taste sweeter.

More recently, machine learning has...