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Market Basket Analysis: Building Association Rules

RetailAssociation rulesRecommandation engineMarket basket analysisMBA
+8
patmuell profile image
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Jun 3, 2024 12:47 PM
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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

External resources

  • Market Basket Analysis and Recommandation Engines
  • Market Basket Analysis and Recommandation Engines
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Used extensions & nodes

Created with KNIME Analytics Platform version 4.5.0
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    KNIME Base nodesTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    knime
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    KNIME Itemset MiningTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    knime
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    KNIME Math Expression (JEP)Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    knime
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    KNIME Quick FormsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    knime

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