what is the difference between Association rule mining & frequent itemset mining

Question

i am new to data mining and confuse about Association rules and frequent item mining. for me i think both are same but i need views from experts on this forum

My questio

Answer 1

Association Rule mining:

Association rule mining is used to find the patterns in data.it finds the features which occur together and correlated.

• Example:

For example, people who buy diapers are likely to buy baby powder. Or we can rephrase the statement by saying: If (people buy diaper), then (they buy baby powder). Note the if, then rule. This does not necessarily mean that if people buy baby powder, they buy diaper. In General, we can say that if condition A tends to B it does not necessarily mean that B tends to A.

Frequent item set mining:

Frequent item set mining is used to find the common item sets in data. it can generate association rules from the given transactional datasets.

• Example:

If there are 2 items X and Y purchased frequently then its good to put them together in stores or provide some discount offer on one item on purchase of other item. This can really increase the sales. For example it is likely to find that if a customer buys Milk and bread he/she also buys Butter. So the association rule is [‘milk]^[‘bread’]=>[‘butter’]. So seller can suggest the customer to buy butter if he/she buys Milk and Bread.