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SPMF 2.36 - 10 new algorithms are released
Posted by:
webmasterphilfv
Date: January 09, 2019 05:32PM
Hello all,
In case, you have not noticed, I have released a new version of SPMF at the begining of the week. SPFM v.2.36 includes 10 new algorithms:
-the CHUI-Miner(Max) algorithm for discovering maximal high utility itemsets in a transaction database with utility information
- the NegFIN and dFIN algorithms for frequent itemset mining (by Nader Aryabarzan et al. )
- the HUIF-PSO, HUIF-GA and HUIF-BA for mining high utility itemsets using particle swarm optimization, a genetic algorithm and a bat algorithm, respectively (by Wei Song, Chaomin Huang et al.)
- the PHUSPM and UHUSPM algorithms for discovering high utility probability sequential patterns in uncertain data (by Jerry Chun-Wei Lin, Ting Li et al.)
- the MEMU algorithm for mining high-average utility itemsets with multiple minimum average utility thresholds (by Jerry Chun-Wei Lin, Shifeng Ren et al.)
- the ProSecCo algorithm for progressive sequential pattern mining with convergence guarantees (thanks to Sacha Servan-Schreiber), which was a runner-up for the best student paper award at ICDM.
Thanks again for using SPMF. If someone is interested in contributing some algorithms to SPMF, just let me know.
Best regards,
Edited 3 time(s). Last edit at 01/09/2019 05:33PM by webmasterphilfv.
In case, you have not noticed, I have released a new version of SPMF at the begining of the week. SPFM v.2.36 includes 10 new algorithms:
-the CHUI-Miner(Max) algorithm for discovering maximal high utility itemsets in a transaction database with utility information
- the NegFIN and dFIN algorithms for frequent itemset mining (by Nader Aryabarzan et al. )
- the HUIF-PSO, HUIF-GA and HUIF-BA for mining high utility itemsets using particle swarm optimization, a genetic algorithm and a bat algorithm, respectively (by Wei Song, Chaomin Huang et al.)
- the PHUSPM and UHUSPM algorithms for discovering high utility probability sequential patterns in uncertain data (by Jerry Chun-Wei Lin, Ting Li et al.)
- the MEMU algorithm for mining high-average utility itemsets with multiple minimum average utility thresholds (by Jerry Chun-Wei Lin, Shifeng Ren et al.)
- the ProSecCo algorithm for progressive sequential pattern mining with convergence guarantees (thanks to Sacha Servan-Schreiber), which was a runner-up for the best student paper award at ICDM.
Thanks again for using SPMF. If someone is interested in contributing some algorithms to SPMF, just let me know.
Best regards,
Edited 3 time(s). Last edit at 01/09/2019 05:33PM by webmasterphilfv.