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- Introduction to the K-Means clustering algorithm (with Java code) | The Data Blog on Categorical data clustering: 25 years beyond K-modes (a survey)
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Category Archives: spmf
Merry X-mas and Happy New Year!
Today, it is just a short blog post to wish happy holidays, merry X-mas and Happy New Year to all users and developers of SPMF, from all around the world! More surprises will come for 2025. I am currently ending … Continue reading
SPMF 2.62 is released!
This is a short blog post to announce that SPMF 2.62 is released, and can be downloaded from the SPMF website‘s download page. The previous version of SPMF (2.60) introduced a lot of new features, also with some code refactoring, … Continue reading
Posted in Data Mining, Data science, open-source, spmf
Tagged association rule, data mining, itemset mining, java, new version, open source, pattern mining, spmf
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Two new shopping datasets with taxonomy
This is just to let you know that I have added two new transaction datasets to the SPMF datasets webpage: Those are two customer transaction datasets obtained by transforming the data from the instacart competition that was held on Kaggle in 2017. … Continue reading
Posted in Database, Pattern Mining, spmf
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SPMF: bug fix about screen resolution
Hi all, this is just to let you know that I found that there was a problem with the user interface of SPMF on low resolution screens in the update 2.60. The table for setting the parameters of algorithms was … Continue reading
Posted in Pattern Mining, spmf
Tagged data mining, open source, pattern mining, software, spmf
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SPMF 2.60 is released!
This is a short message today to announce that the new version of SPMF 2.60 is finally released! This is a major version as it contains many new things. The full lists of changes can be found on the download … Continue reading
Posted in Data Mining, Data science, Java, Pattern Mining, spmf
Tagged algorithms, data mining, data science, fast, implementations, java, open source, pattern mining, software, spmf
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How to download an offline copy of the SPMF documentation?
Today, I will show you how to download an offline copy of the SPMF documentation. In the upcoming version 2.60 of SPMF, you can run this algorithm to open the windows of developpers tools: Then you can click here to … Continue reading
Posted in spmf
Tagged data mining, documentation, java, pattern mining, python, software, spmf
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Some interesting statistics about SPMF
While I am preparing the next version of Java SPMF data mining software (2.60), here are some interesting statistics about the project, that I have generated directly from the metadata provided by SPMF. Here it is: The number of algorithms … Continue reading
Posted in Data Mining, Data science, spmf
Tagged big data, data mining, data science, itemset mining, pattern mining, spmf
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Sneak peak at the new user interface of SPMF (part 3)
Today, I would like to talk to you about another upcoming feature of the next version of SPMF (2.60), which will be released soon. It will be a Workflow Editor that will allow the user to select multiple algorithms from … Continue reading
Posted in Data Mining, open-source, spmf
Tagged algorithm, association rule, data, data mining, graph mining, gui, itemset, pattern, pattern mining, sequential pattern mining, spmf
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Sneak peak at the new user interface of SPMF (part 2)
Today, I will continue to show you some upcoming features of SPMF 2.60, on which some work is ongoing. This new version of SPMF should be released in the coming weeks. The new feature that I will talk about today … Continue reading
Posted in spmf
Tagged algorithm, data mining, episode, episode mining, event sequence, open source, pattern mining, patterns, spmf, time interval data, timeline, timeline viewer, tirp, visualization
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Sneak peak at the new user interface of SPMF (part 1)
I am currently working on the next version of SPMF, which will be called 2.60. There will be several improvements to the user interface of SPMF. Here is an overview of some of the improvements to give you a sneak … Continue reading
Posted in Big data, Data Mining, Data science, spmf
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