This is a transactionaldata set,which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.The company mainly sells unique all-occasion gifts. Many customers of the company are wholesalers.
Dataset
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Attribute Information:
InvoiceNo: Invoice number. Nominal, a 6-digit integral number uniquely assigned to each transaction. If this code starts with letter 'c', it indicates a cancellation.
StockCode: Product (item) code. Nominal, a 5-digit integral number uniquely assigned to each distinct product.
Description: Product (item) name. Nominal.
Quantity: The quantities of each product (item) per transaction. Numeric.
InvoiceDate: Invice Date and time. Numeric, the day and time when each transaction was generated.
UnitPrice: Unit price. Numeric, Product price per unit in sterling.
CustomerID: Customer number. Nominal, a 5-digit integral number uniquely assigned to each customer.
Country: Country name. Nominal, the name of the country where each customer resides.
Tasks:
a. Run apriori algorithm on the dataset to find out all frequent itemsets with support of 3%. (2.5)
b. Find association rules with support 3% and confidence 30%. (2.5)
c. Find out the maximum itemsets based on a. (2)
d. Find out the top-10 frequent items with the highest support. (3)
What to submit.
a. Your code.
b. Descriptions of the proposed solutions of the tasks.
c. Outputs.
data is provided but cant uplaod file because its more than 25 mb how can I upload to u