What is Association Learning?
Association learning is a rule based machine learning and data mining technique that finds important relations between variables or features in a data set. Unlike conventional association algorithms measuring degrees of similarity, association rule learning identifies hidden correlations in databases by applying some measure of interestingness to generate an association rule for new searches.
How Does Association Learning Work?
Association rule algorithms count the frequency of complimentary occurrences, or associations, across a large collection of items or actions. The goal is to find associations that take place together far more often than you would find in a random sampling of possibilities. This rule-based approach is a fast and powerful tool for mining categorized, non-numeric databases.
A classic example of this system in practice is analyzing retail sales to find the best way to place items in a store. In a store with a million transactions a year, 10,000 sales might include newborn baby diapers and 100,000 include razor blades. At first glance, newborn diapers and razors seem statistically independent, with no apparent correlation. But rule mining would dig deeper into the transaction frequency and find out that 5,000 sales include both items.
So instead of simply learning that 1% of shoppers buy diapers and 10% buy razor blades, the association system generates a new rule that 50% of all shoppers purchasing newborn diapers will also buy razor blades, which can be beneficial information for marketing campaigns.
Just as important, the rule-based approach enhances performance and generates new rules as it analyzes more data. With a large enough dataset, this allows the machine to mimic the human brain’s feature extraction and abstract association capabilities from raw data.The same basic technique has countless other applications as well
Practical Uses of Association Learning
• Basket data analysis – Whether planning product placement in a storefront, running a marketing campaign or designing a business catalog, association mining is a useful tool to take the guesswork out of what your customers are looking for.
• Web usage mining and intrusion detection – Finding these hidden correlations is a powerful predictive tool to discover brand new security threats and network performance issues that haven’t been analyzed first by a human.
• Bioinformatics – From biology to engineering and everything in between, association mining is one of the go-to foundational tools for spotting overlooked and potentially useful techniques.
