Characteristics of Market Basket Analysis

Both independent and dependent data are nominal or categorical type. Therefore, what we can do is only count the frequency of pattern. Market basket analysis is sometimes called as Mining Frequent Pattern. If the data are quantitative, it would be categorized into some interval (but the meaning is actually nominal) such as: age 0 to 1, age 1-5, age 5 to 12, age 12 to 19, etc.

In Market Basket Analysis, we usually do not consider about the number of each items that the customers bought. Whether a customer buys one kg of apple or 10 kg of apple would be considered as the same set of apple.

We do not use all transactions that are recorded. Only transactions of purchase of more than one item are considered as data. Transactions of single item are not used for the analysis.

The input data are assumed to be clean from error and noise.

Unlike the simple demonstration example here, the binarized transaction record is usually a sparse matrix (matrix with many zeros) because of very large number of transactional record and number of items. Computation and storing sparse matrix requires special algorithm.

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