What is the Apriori principle?

Put simply, the apriori principle states that. if an itemset is infrequent, then all its supersets must also be infrequent. This means that if {beer} was found to be infrequent, we can expect {beer, pizza} to be equally or even more infrequent.

What are the two principles of Apriori algorithm?

This algorithm uses two steps “join” and “prune” to reduce the search space. It is an iterative approach to discover the most frequent itemsets.

What is difference between Apriori and FP growth?

Apriori uses candidate generation where frequent subsets are extended one item at a time. FP-growth generates conditional FP-Tree for every item in the data. Since apriori scans the database in each of its steps it becomes time-consuming for data where the number of items is larger.

What are the working principle of Apriori algorithm explain with a suitable example?

The Apriori algorithm uses frequent itemsets to generate association rules, and it is designed to work on the databases that contain transactions. With the help of these association rule, it determines how strongly or how weakly two objects are connected.

Where is Apriori algorithm used?

Apriori algorithm is a classical algorithm in data mining. It is used for mining frequent itemsets 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.

How would you explain the principle of Apriori algorithm How can the efficiency of an Apriori algorithm be improved?

To improve the efficiency of level-wise generation of frequent itemsets, an important property is used called Apriori property which helps by reducing the search space. All subsets of a frequent itemset must be frequent(Apriori propertry). If an itemset is infrequent, all its supersets will be infrequent.

Why Apriori algorithm is used for market basket analysis?

Apriori Algorithm is a widely-used and well-known Association Rule algorithm and is a popular algorithm used in market basket analysis. It helps to find frequent itemsets in transactions and identifies association rules between these items. The limitation of the Apriori Algorithm is frequent itemset generation.

How is apriori algorithm used in daily life?

Apriori Algorithm usually contains or deals with a large number of transactions. For example, customers buying a lot of goods from a grocery store, by applying this method of the algorithm the grocery stores can enhance their sales performance and could work effectively.

What is the advantage of apriori algorithm?

The advantages of apriori are as follows: This is the most simple and easy-to-understand algorithm among association rule learning algorithms. The resulting rules are intuitive and easy to communicate to an end user.

Is Apriori algorithm supervised or unsupervised?

Is this supervised or unsupervised? Apriori is generally considered an unsupervised learning approach, since it’s often used to discover or mine for interesting patterns and relationships. Apriori can also be modified to do classification based on labelled data.