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New version of SPMF: 2.34 - five new algorithms
Date: October 02, 2018 08:31AM
This is to let you know that a new version of SPMF has been released.
The main changes are as follows:
3 new algorithm implementations by Siddharth Dawar, Vikram Goyal et al.:
- HMDS algorithms for mining the top-k high utility itemsets in a data stream
- HMiner for high utility itemset mining
- UP-Hist for high utility itemset mining
1 algorithm implementation by Cheng Wei Wu et al.
- the DFI-Growth for recovering all frequent itemsets from frequent closed itemsets (thanks to Cheng-Wei Wu et al.)
1 other algorithm implementation (obtained under GPL license)
- the Skopus algorithm for mining the top-k sequential patterns with leverage
Besides, a bug was fixed in the MinFHM algorithm (thanks to Hung Nguyen for finding and fixing the bug)
Are you curious about what will be in the next version? We are currently working on an improved user interface with a new plugin system. Besides, some other algorithms will be added soon such as GSpan, OpusMiner, and others.
Thanks again to all for your support and for contributing and citing SPMF. This is what makes this project continue to grow.
Edited 3 time(s). Last edit at 10/02/2018 08:37AM by webmasterphilfv.