Icon

04_​Association_​Rules_​for_​MarketBasketAnalysis

Market Basket Analysis: Building Association Rules

This workflow builds a recommandation engine for market basket analysis using the Borgelt version of the Apriori algorithm.

URL: Market Basket Analysis and Recommandation Engines https://www.knime.org/knime-applications/market-basket-analysis-and-recommendation-engines
URL: Market Basket Analysis and Recommandation Engines https://www.knime.org/blog/market-basket-analysis-and-recommendation-engines

Market Basket Analysis: Build Association Rules 1. Read Transaction/Basket data and Product data 2. Using "A priori" algorithm, build association rule set - min. set size = 1 - min rule confidence = 10% - min support is controlled by Double Input Quickform node in % 3. Translate Antecedent collections into product name concatenations 4. Translate Consequent Item ID into Consequent Product Name 5. Calculate price stats and rule revenue 6. Write assciation rule set to file Read data1. Transactions2. Productscalculate association rules("A priori" algorithm)- translate antecedent collectionto product name concatenations- associate consequent product ID to product name- calculate price stats and rule revenueset MinimumSupportwrite association rulesto a file Read HistoricalBasket Data Association RuleLearner (Borgelt) Ungroup collections DoubleConfiguration Table Writer Market Basket Analysis: Build Association Rules 1. Read Transaction/Basket data and Product data 2. Using "A priori" algorithm, build association rule set - min. set size = 1 - min rule confidence = 10% - min support is controlled by Double Input Quickform node in % 3. Translate Antecedent collections into product name concatenations 4. Translate Consequent Item ID into Consequent Product Name 5. Calculate price stats and rule revenue 6. Write assciation rule set to file Read data1. Transactions2. Productscalculate association rules("A priori" algorithm)- translate antecedent collectionto product name concatenations- associate consequent product ID to product name- calculate price stats and rule revenueset MinimumSupportwrite association rulesto a fileRead HistoricalBasket Data Association RuleLearner (Borgelt) Ungroup collections DoubleConfiguration Table Writer

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: rosy
Created at: 2015-03-23
On NodePit since: 2024-04-10
Last update: 2024-12-17
Created with KNIME version: v5.2.3
Tags: retailassociation rulesrecommandation enginemarket basket analysisMBAApriori algorithmBorgeltdata collectionQuickformsupply chainretailrecommendation engineTheGuideBookGIDS

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!