Most data mining methods assume that the data set processed is a collection of rows of data, where each row consists of a fixed number of attributes. In the data set in the form of record data, there is no relationship between the data line one with the other data lines, and also with other data sets. Each row of data stands interconnected using a key, but in the data set in the form of record data, it is assumed that there is only one table containing a number of rows of data. Therefore, usually the data set processed in the data mining is the output of the data warehouse system that uses the query to perform data retrieval of a number of tables in the system set of data entered in the type of record data, including market basket data and matrix data.
Market basket data is a special type of record data, where each transaction record contains a number of items, and the number of items for a transaction can be different from other transactions. Examples can be seen in the case of Market basketball data market, every buyer makes a purchase of goods that amount and type can be different from asymmetric buyers. Asymmetric is The order of values from the first to last column may vary from one transaction to another. Usually, each attribute with value 1 for the purchased item is represented by a binary value, and 0 for goods not purchased.
Market basket data is a special type of record data, where each transaction record contains a number of items, and the number of items for a transaction can be different from other transactions. Examples can be seen in the case of Market basketball data market, every buyer makes a purchase of goods that amount and type can be different from asymmetric buyers. Asymmetric is The order of values from the first to last column may vary from one transaction to another. Usually, each attribute with value 1 for the purchased item is represented by a binary value, and 0 for goods not purchased.
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