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02_​Build_​Association_​Rules_​for_​MarketBasketAnalysis

Market Basket Analysis: Building Association Rules - exercise
Exercise: Market Basket Analysis: Build Association RulesThis workflow reads transaction/basket data and product data. The goal is to extract association rules based on thetransaction/basket data.1) Use the Association Rule Learner node to calculate the association rules with the following settings:- min rule confidence = 10%- min support 2.5- Leave other settings to their defaults2) Translate the product IDs in the antecedent collection and the consequence to product names by applying the Translate Product Ids to Product Names metanode. Read dataTop: TransactionsBottom: Productswrite association rulesto a fileTop: Association rulesBottom: Lookup table Products and Product Ids Read HistoricalBasket Data Table Writer Translate Product Idsto Product Names Exercise: Market Basket Analysis: Build Association RulesThis workflow reads transaction/basket data and product data. The goal is to extract association rules based on thetransaction/basket data.1) Use the Association Rule Learner node to calculate the association rules with the following settings:- min rule confidence = 10%- min support 2.5- Leave other settings to their defaults2) Translate the product IDs in the antecedent collection and the consequence to product names by applying the Translate Product Ids to Product Names metanode. Read dataTop: TransactionsBottom: Productswrite association rulesto a fileTop: Association rulesBottom: Lookup table Products and Product Ids Read HistoricalBasket Data Table Writer Translate Product Idsto Product Names

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Created by: rosy
Created at: 2015-03-23
On NodePit since: 2022-11-15
Last update: 2024-04-27
Created with KNIME version: v4.6.1
Tags: retailassociation rulesrecommandation enginemarket basket analysisMBAApriori algorithmBorgeltdata collectionQuickformsupply chainretailrecommendation engine

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