The Altair Community is migrating to a new platform to provide a better experience for you. In preparation for the migration, the Altair Community is on read-only mode from October 28 - November 6, 2024. Technical support via cases will continue to work as is. For any urgent requests from Students/Faculty members, please submit the form linked here

How to increase the accuracy of the classifiers?

haziqros_97haziqros_97 Member Posts: 5 Learner II
Hye everyone!

I really need your help. I am doing my thesis research using RM. My supervisor asked me to use Turbo Prep. The issue I faced now is the accuracy of the classifiers is below 70%. My supervisor wanted me to get above 80%, if possible. Can you guys give me some tips on how to increase the accuracy?

Thanks in advance.

Best Answer

  • lionelderkrikorlionelderkrikor RapidMiner Certified Analyst, Member Posts: 1,195 Unicorn
    Solution Accepted
    @haziqros_97,

    You can find here a process with a performance strictly greater to 70 % using : 
     - Smote upsampling
     - feature engineering

    Feel free to increase the time limit associated to the Automatic Feature Engineering operator (currently se to 180 seconds).

    I think that to reach 80 % accuracy will be extremely difficult, maybe impossible...
    Keep in mind that the accuracy is not the only criteria (the "Kaggle syndrom") to choose a model, you have to take into account  : 
     - the simplicity of the model
     - the interpretability of the model
     - the capacity to "generalize" of the model...

    Hope this helps,

    Regards,

    Lionel

Answers

  • lionelderkrikorlionelderkrikor RapidMiner Certified Analyst, Member Posts: 1,195 Unicorn
    HI @haziqros_97,

    wide subject !!!

    You can  : 

     - preprocess /clean your data : impute missing value, replace rares values etc.
     - perform feature engineering (feature selection/feature generation)
     - try different models (NB, neural networks, Decision tree)
     - optimize the parameters of the best model (using Optimize Parameters operator)

    and ideally perform a Cross Validation to evaluate the accuracy of your models. It is considered as a best practice, representative of the performance of your model(s) on future unseen data.

    I hope it helps  !

    Regards,

    Lionel

    PS : Note that all the 4 steps described above can be automatically performed by AutoModel inside RapidMiner...
  • haziqros_97haziqros_97 Member Posts: 5 Learner II
    Hi mate, thanks a lot for answering my question. I try it first. Later I'll get back to you.
  • haziqros_97haziqros_97 Member Posts: 5 Learner II
    edited August 2021
    Sorry mate. I have tried as you said but the accuracy is still the same. Here I attach my original data before I cleaned it. Hopefully, someone can help me to do this and get the accuracy above 80%. 
    Please help me, guys. 

    Thanks in advance.
  • lionelderkrikorlionelderkrikor RapidMiner Certified Analyst, Member Posts: 1,195 Unicorn
    @haziqros_97

    What is the label in your dataset ?

    Lionel


  • haziqros_97haziqros_97 Member Posts: 5 Learner II
    SPM performance for English and Mathematics.
  • lionelderkrikorlionelderkrikor RapidMiner Certified Analyst, Member Posts: 1,195 Unicorn
    @haziqros_97,

    And an other process using the same preprocessing steps described above, but using the deep-learning library....

    Hope this helps,

    Regards,

    Lionel
  • haziqros_97haziqros_97 Member Posts: 5 Learner II
    Thanks lad for answering. Wishing you best of luck.
Sign In or Register to comment.