New version of SPMF (2.44): 4 new algorithms, datasets and features

Today, I am happy to announce that a new version of the SPMF open-source data mining software is released (v. 2.44). This is the download page. This new version was made possible due to several contributors.

SPMF

What is new?

New data mining algorithms:
– LTHUI-Miner for mining the locally-trending high utility itemsets (by Yanjun Yang)
– MLHUI-Miner for discovering the multi-level high utility itemsets (by Ying Wang)
– AER-Miner for mining attribute evolution rules in a dynamic attributed graph (by Ganghuan He)
– TSPIN for mining the top-k stable periodic patterns in a transaction database
(by Ying Wang, Peng Yang)

New datasets:
Fruithut, Liquor and E-commerce (prepared by Ying Wang)

Some bug fixes:
– Fixed a small bug in DFIN (thanks to Nader Aryabarzan)
– Fixed a bug in the user interface for TKG (thanks to..)
– Fixed a small error in the DB_LHUI.txt example file

Some new tool:
– Added a new tool to fix problems in transactions databases with time and utility information

Some new feature:
– Added a feature for saving or loading a trained sequence prediction model from file (for the AKOM, DG, TDAG, LZ78, PPM, CPT, and CPT+ algorithms)

Wrappers for other languages
– Added a webpage with a list of wrappers for calling some SPMF algorithms from R, Python, Weka and Spark (note: those wrappers were designed by other people and are not an official project of SPMF so be aware that not all algorithms may work… but I think it can be quite useful for some)

What is for the future?

The SPMF project is still under active development. The next version will be released in a few weeks as I still have received several algorithms that are waiting to be added to SPMF. The next release will include several new sequential pattern mining algorithms.

Would you like to contribute to SPMF?

The SPMF project is quite successful due to the numerous contributors that are provided some code, reported bugs and also provided many comments. If you are interested to contribute something (code of some algorithms or other things), please leave me an e-mail at philfv8 AT yahoo DOT com.

Thanks again to all for your support!

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