Apriori Algorithm (Associated Learning) – Fun and Easy Machine Learning
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The Apriori algorithm is a classical algorithm in data mining that we can use for these sorts of applications (i.e. recommender engines). So It is used for mining frequent item sets and relevant association rules. It is devised to operate on a database containing a lot of transactions, for instance, items brought by customers in a store.
It is very important for effective Market Basket Analysis and it helps the customers in purchasing their items with more ease which increases the sales of the markets. It has also been used in the field of healthcare for the detection of adverse drug reactions.
A key concept in Apriori algorithm is that it assumes that:
1. All subsets of a frequent item sets must be frequent
2. Similarly, for any infrequent item set, all its supersets must be infrequent too.
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