The Altair Community and the RapidMiner community is on read-only mode until further notice. Technical support via cases will continue to work as is. For any urgent requests from Students/Faculty members, please submit the form linked here.
Options
Student Dataset is giving different classification accuracy using cross validation on RapidMiner 9.6
![VikasRattan](https://us.v-cdn.net/6030995/uploads/defaultavatar/nCCNNSPK1YM69.jpg)
![](https://s3.amazonaws.com/rapidminer.community/vanilla-rank-images/learner-16x16.png )
in Help
Student Dataset is giving different classification accuracy using cross validation on RapidMiner 9.6(educational version)
0
Best Answer
-
Options
varunm1 Moderator, Member Posts: 1,207
Unicorn
Try to run the attached process without changing multiple times as see the results. I enable random seed for SMOTE, Cross-Validation & random tree. You can import this process by going to File --> Import process. You need to set a random seed for all operators that have that option. A random seed will help generate the same data all the time and even in the random tree, it will do the same randomization. These are critical to producing reproducible results.
Let me know if you still have issues.Regards,
Varun
https://www.varunmandalapu.com/Be Safe. Follow precautions and Maintain Social Distancing
1
Answers
Did you set "Random Seed" option in cross-validation? If not, your folds might be divided differently during different runs. Also which algorithm are you using inside cross-validation?
Varun
https://www.varunmandalapu.com/
Be Safe. Follow precautions and Maintain Social Distancing
Varun
https://www.varunmandalapu.com/
Be Safe. Follow precautions and Maintain Social Distancing
File is attached.