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Team, Is there a plan to implement ML.fpm (Frequent Pattern Mining) anytime soon? It has only 2 algorithms as per Spark v3.1.2 (FP-Growth & PrefixSpan) and are very useful ML algorithms in some scenarios. Would be a great help if it's a part of this library.
Thanks.
The text was updated successfully, but these errors were encountered:
We reached a critical stage for one of our offering that depends on this library along with SparkML / MLLib features. Without full features that are present in the current supported versions of Spark (by this library), we are limited to just using this for some ETL pipelines with SparkSQL. It would be a great help if there's a published plan for the future implementations or otherwise some guidance on how to easily integrate other language bindings (as per #33 ) so that we can determine how much we can leverage this library for our scenarios.
It's been an year this request is raised! Can we expect implementation of this feature any time sooner? There's also a pending pull request (#1096 ) for review. Please let us know if there is any timeline for these features implementation so that we can make a decision to use this library or switch to other languages (Java/Scala).
Team, Is there a plan to implement ML.fpm (Frequent Pattern Mining) anytime soon? It has only 2 algorithms as per Spark v3.1.2 (FP-Growth & PrefixSpan) and are very useful ML algorithms in some scenarios. Would be a great help if it's a part of this library.
Thanks.
The text was updated successfully, but these errors were encountered: