Market Basket Analysis using Association Rule-Mining in R language
Association mining is usually done on transactions data from a retail market or from an online e-commerce store. Since most transactions data is large, the apriori algorithm makes it easier to find these patterns or rules quickly. Association Rules are widely used to analyze retail basket or transaction data, and are intended to identify strong rules discovered in transaction data using measures of interestingness, based on the concept of strong rules. Apriori uses a "bottom up" approach, where frequent subsets are extended one item at a time (a step known as candidate generation), and groups of candidates are tested against the data. The algorithm terminates when no further successful extensions are found. DATASET: Groceries_dataset Let's code and analyse the algorithm 💪 👉 Import the groceries dataset 👉Explore the data 👉 Perform data preparation such as checking the Null values, normalising the format of data to numeric values and group the data of similar values