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Why would you use Python instead of RapidMiner?

User: "Mariusz"
New Altair Community Member
Updated by Jocelyn
Hello! I am doing degree in AI engineering and I've been assigned task of comparing RapidMiner to Python. While I'm not a Python beginner, I'm fairly new to the RapidMiner and I definitely lack industrial experience. Given my limited knowledge, I still find RapidMiner superior in carrying out tasks I would usually code in Python. So my question is: In what circumstances, or for what specific task you would use Python instead of RapidMiner, and why?
Cheers, Mariusz.

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    User: "lionelderkrikor"
    New Altair Community Member
    Accepted Answer
    Hi Mariusz,

    First, in introduction, I recall that you can integrate Python scripts inside RapidMiner, via the Execute Python operator (via Python Scripting extension to install from the marketplace)  .
    By this way, you can benefit of some Python feature(s) inside RapidMiner.
    Now, to answer to your question, I personnaly envisage to use Python for 3 tasks for potential future projects : 

    1.  Use models/algorithms which are not implemented in RapidMiner. I'm thinking especially to 2 performing algorithms : 
    •   Light GBM
    •   XGBoost
         2.  For a project involving time series, I envisage to use TSFRESH a python package which automatically calculates a large number (dozens) of time series caracteristics (including complex caracteristics), the so called features. In comparaison RapidMiner has the Extract Aggregates operator but it calculates around 12 features.

         3. For image mining, there is no "out of the box" solution implemented in RapidMiner, for example to read directly an image.
             So, for image/video processing ,  I'm using OpenCV a powerful python package dedicated to this task.

    Hope this helps,

    Regards,

    Lionel

    PS : If, of course, one or more feature(s) I have described in this post are already implemented in RapidMiner, thanks to correct me and explain how to  access it (them).


    User: "kypexin"
    New Altair Community Member
    Accepted Answer
    Hi @Mariusz

    I work in the field of credit risk and scoring, so that's exactly my case for now:
    • Not all domain specific algorithms even exist in RM, for example weight of evidence and information value algorithms.
    • In production, there's a legacy system based on AWS docker and specific Python code, which uses lambda function to deploy web services in production. 
    That's why I use RM first for quick data cleaning and model prototyping, and then I move everything to Python, including training production models as well (which are serialised via pickle) and then creating a web service for deploying on AWS.

    So in general, that's in many aspects a question of legacy production systems and a whole IT ecosystem in the organisation. When I was once creating a fraud detection engine from scratch using RM, that was a perfectly closed ecosystem which didn't need anything except RM itself.