Database Reference
In-Depth Information
Chapter 1
Introduction to Decision Trees
1.1 Data Science
Data Science is the discipline of processing and analyzing data for the
purpose of extracting valuable knowledge. The term “Data Science” was
coined in the 1960's. However, it really took shape only recently when
technology has become suciently mature.
Various domains such as commerce, medicine and research are applying
data-driven discovery and prediction in order to gain some new insights.
Google is an excellent example of a company that applies data science on a
regular basis. It is well-known that Google tracks user clicks in an attempt
to improve the relevance of its search engine results and its ad campaign
management.
One of the ultimate goals of data mining is the ability to make
predictions about certain phenomena. Obviously, prediction is not an easy
task. As the famous quote says, “It is dicult to make predictions, especially
about the future” (attributed to Mark Twain and others). Still, we use
prediction successfully all the time. For example, the popular YouTube
website (also owned by Google) analyzes our watching habits in order to
predict which other videos we might like. Based on this prediction, YouTube
service can present us with a personalized recommendation which is mostly
very effective. In order to roughly estimate the service's eciency you could
simply ask yourself how often watching a video on YouTube lead you to
watch a number of similar videos that were recommended to you by the
system? Similarly, online social networks (OSN), such as Facebook and
LinkedIn, automatically suggest friends and acquaintances that we might
want to connect with.
Google Trends enables anyone to view search trends for a topic across
regions of the world, including comparative trends of two or more topics.
1
