Introduction Many business enterprises accumulate large quantities of data from their day-to-day operations. For example, huge amounts of customer purchase data are collected daily at the checkout counters of grocery stores. Table 1 illustrates an example of such data, commonly known as market basket transactions. Each row in this table corresponds to a transaction, which […]
Unit 4: Association Analysis
Study Notes Nepal Posted in 8th Semester, BIMTagged Association Analysis, Basics and Algorithms, bim 8th semester, data mining and data warehousing, Data Mining and Data Warehousing notes, FP-Growth, FP-Tree, Frequent Itemset Pattern & Apriori Principle, Handling Categorical Attributes, study notes nepalLeave a Comment on Unit 4: Association Analysis