Unsupervised machine learning does not use annotated data; that is, the dataset does to contain anticipated results. While there are several unsupervised learning algorithms, we will demonstrate the use of association rule learning to illustrate this learning approach.
Association rule learning is a technique that identifies relationships between data items. It is part of what is called market basket analysis. When a shopper makes purchases, these purchases are likely to consist of more than one item, and when it does, there are certain items that tend to be bought together. Association rule learning is one approach for identifying these related items. When an association is found, a rule can be formulated for it.
For example, if a customer buys diapers and lotion, they are also likely to buy baby wipes. An analysis can find these associations and a rule stating the observation can be formed. The rule would be expressed as {diapers, lotion...