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Solution 5 Training the Apriori Algorithm

Solution 5 Training the Apriori Algorithm
Task 1: Train a music recommendation engine with the Apriori algorithm1. Create a list of artists listened for each user ID2. Train the Apriori algorithm on the created lists with the default settings3. Decrease the minimum support to 0.1 and increase the minimum confidence to 0.9 Task 2: Generate music recommendations1. Select some artists in the configuration dialog of the "Select Artist" component2. Retrieve the matching antecedents of the existing association rules. Allow mismatches if necessary. 3. Join the matched antecedents with the consequences and statistics of the generated association rules4. Select the top recommendation based on the maximum support and confidence Readartists.csvgroup artistsby user IDfind recommendationsadd statisticsrankrecommendations CSV Reader GroupBy AssociationRule Learner Subset Matcher Joiner Top k Selector Select Artist Task 1: Train a music recommendation engine with the Apriori algorithm1. Create a list of artists listened for each user ID2. Train the Apriori algorithm on the created lists with the default settings3. Decrease the minimum support to 0.1 and increase the minimum confidence to 0.9 Task 2: Generate music recommendations1. Select some artists in the configuration dialog of the "Select Artist" component2. Retrieve the matching antecedents of the existing association rules. Allow mismatches if necessary. 3. Join the matched antecedents with the consequences and statistics of the generated association rules4. Select the top recommendation based on the maximum support and confidence Readartists.csvgroup artistsby user IDfind recommendationsadd statisticsrankrecommendations CSV Reader GroupBy AssociationRule Learner Subset Matcher Joiner Top k Selector Select Artist

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Created by: maarit.widmann
Created at: 2022-03-28
On NodePit since: 2022-04-01
Last update: 2024-12-17
Created with KNIME version: v4.5.2
Tags: educationL4-ML

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