What is lift in association rule mining? Converting the data frame into lists. So we need to convert the data into a list of lists.

With the help of these association rule, it determines how strongly or how weakly two objects are connected. Apriori Algorithm in Machine Learning. This algorithm uses a breadth-first search and Hash Tree to calculate the itemset associations efficiently.
A set of items together is called an itemset. If any itemset has k-items it is called a k-itemset. An itemset consists of two or more items.
Thus frequent itemset mining is a data mining technique to identify the items that often occur together. For Example, Bread and butter, Laptop and Antivirus software, etc. See full list on softwaretestinghelp. Frequent itemset or pattern mining is broadly used because of its wide applications in mining association rules, correlations and graph patterns constraint that is based on frequent patterns, sequential patterns, and many other data mining tasks.
Many methods are available for improving the efficiency of the algorithm. Hash-Based Technique:This method uses a hash-based structure called a hash table for generating the k-itemsets and its corresponding count. It uses a hash function for generating the table. Transaction Reduction:This method reduces the number of transactions scanning in iterations.