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Bagging optmization reduced performance
Hi,
I am running an attached dataset to measure the performance of the model. Decision tree gave me a good accuracy value, however, when I used a bagging operator to increase the performance of the model, the output reduced the performance accuracy.
Could anyone help me with what changes I need to make in the model so that accuracy is optimized?
Note: dataset has no attribute tables, uncheck "first row as names" and column operator value to "," while importing the dataset.
Regards,
RT
I am running an attached dataset to measure the performance of the model. Decision tree gave me a good accuracy value, however, when I used a bagging operator to increase the performance of the model, the output reduced the performance accuracy.
Could anyone help me with what changes I need to make in the model so that accuracy is optimized?
Note: dataset has no attribute tables, uncheck "first row as names" and column operator value to "," while importing the dataset.
Regards,
RT
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Answers
this sounds like you overtrained your decision tree. Did you check for it?
Best,
Martin
Dortmund, Germany
As @mschmitz said, it might be due to overfitting. DId you try hyperparameter optimization using "optimize parameter grid operator"? You can search for the best hyperparameters for your algorithm and reduce overfitting.Â
Varun
https://www.varunmandalapu.com/
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