DEVELOPMENT OF ASSOCIATION RULE FRAMEWORK USING PARTICLE SWARM OPTIMIZATION ON FP-GROWTH WEIGHTED FREQUENT ITEMSET MINING
This research develops an association rule framework based on optimizing the minimum support value, minimum confidence, and applying weights to items using a combination of PSO and WFIM algorithms in the FP-Growth algorithm. This research is designed to overcome the limitations in determining the mi...
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| Main Author: | |
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/87708 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
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