This workflow builds a recommandation engine for market basket analysis using the Borgelt version of the Apriori algorithm. 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
Used extensions & nodes
Created with KNIME Analytics Platform version 4.3.1
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