Hello Processing - Vula

An Introduction To Programming With Processing
small data set with a high ratio of inconsistent data types, manual data mining
could be more effective and save you some time.
For example, lets take a hypothetical situation where the owner of a small café
has asked you to determine what items a customer is likely to purchase together.
The data set you have acquired consists of all the items customers have purchased
in the store over the past year. From that data you could determine that goods can
be divided up into food, drinks, magazines, stationary etc, and then into even
smaller groups like fruit, vegetables, soft-drinks etc. Identifying these groups
would be the first step of data mining and is a process also known as clustering. If
the café has a large variety of items to choose from the clusters making up the
data could resultantly be numerous, yet the data set as a whole is actually quite
small, only consisting of a single year of purchased items.
In contrast a more established café that has been operating for several years
proposes the same question to you. In the case of the smaller café groupings of
purchased items would yield a lower probability of repeating in a shorter period
of time. In contrast the more established café has a better chance of the same
groups of items being purchased together over a longer period of time.
In the former case manually mining this data set could be more effective because
of the lower probability of the same items being purchased together in a relatively
short space of time. In this scenario the majority of your time would be spent on
clustering and populating the resultant groups after eliminating the majority of
items purchased in that year because they will not fall into any cluster.
However in the case of the established café although there may be just as many
clusters the values that these clusters are populated with have a higher probability
of being repeated, it might therefore be more efficient to have a computer
program count, cluster and mine the data.
Regardless of whether you choose to manually mine your data or have a software
program do the work for you, you should have a set of data at the end of the
process that can be manipulated programmatically.
A Scalable Software Development Model 30