ABSTRACT
Suppose that you have a website selling software that you’ve written. You want to make the website more personalised to the user, so you start to collect data about visitors, such as their computer type/operating system, web browser, the country that they live in, and the time of day they visited the website. You can get this data for any visitor, and for people who actually buy something, you know what they bought, and how they paid for it (say PayPal or a credit card). So, for each person who buys something from your website, you have a list of data that looks like (computer type, web browser, country, time, software bought, how paid). For instance, the first three pieces of data you collect could be:
ˆ Macintosh OS X, Safari, UK, morning, SuperGame1, credit card
ˆ Windows XP, Internet Explorer, USA, afternoon, SuperGame1, PayPal
ˆ Windows Vista, Firefox, NZ, evening, SuperGame2, PayPal
Based on this data, you would like to be able to populate a ‘Things You Might Be Interested In’ box within the webpage, so that it shows software that might be relevant to each visitor, based on the data that you can access while the webpage loads, i.e., computer and OS, country, and the time of day. Your hope is that as more people visit your website and you store more data, you will be able to identify trends, such as that Macintosh users from New Zealand (NZ) love your first game, while Firefox users, who are often more knowledgeable about computers, want your automatic download application, etc. Once you have collected a large set of such data, you start to examine it and
work out what you can do with it. The problem you have is one of prediction: given the data you have, predict what the next person will buy, and the reason that you think that it might work is that people who seem to be similar often act similarly. So how can you actually go about solving the problem? This is one of the fundamental problems that this book tries to solve. It is an example of what is called supervised learning, because we know what the right answers are for some examples (the software that was actually bought) so we can give the learner some examples where we know the right answer. We will talk about supervised learning more in Section 1.3.
