Clustering-based speed-up technique in ARM
This submission is to support submission of the corresponding manuscript:
https://www.researchgate.net/publication/343221822
The contribution of the manuscript is a novel speed-up technique, which application speeds-up association rule mining (ARM). The catchy feature of this technique is that it works well in fuzzy ARM and doesn't work well in non-fuzzy ARM.
NOTES:
(A)
Unfortunately, this time, the toolbox has no tutorial or video instruction. Possibly, it will be added later.
(B)
The toolbox has 6 scripts to be launched in the following order:
1) Initial_dataset_processing % the script performs clustering to obtain a reduced-size "Data_KM_Final_Set.txt".
2) Initial_dataset_formalization % the script prepares a dataset for further ARM.
3) MF_Show % the script plots the results of partitioning.
4) Critical_C=???? % the operation defines minsupp.
5) Entire_Ruleset_Design % the script performs ARM.
6) FIS_Design % the script creates a Mamdani-Type FIS from the ARM results.
7) FIS_Running % the created FIS is tested on selected data.
Cite As
Vugar (2024). Clustering-based speed-up technique in ARM (https://www.mathworks.com/matlabcentral/fileexchange/73104-clustering-based-speed-up-technique-in-arm), MATLAB Central File Exchange. Retrieved .
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Acknowledgements
Inspired: Data reduction technique in fuzzy association rule mining
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