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My honest testing performance is greater than training performance? is it luck or incorrect
I have used split operator on my data source in the ratio of 4:1 for training and honest testing I am using DT and cross-validation.
The performance result for testing is accuracy 93.21%, kappa 0.863 and for training accuracy 93.97%, kappa 0.695
I need to know whether the model is underfitting data and how should I conclude this result
The performance result for testing is accuracy 93.21%, kappa 0.863 and for training accuracy 93.97%, kappa 0.695
I need to know whether the model is underfitting data and how should I conclude this result
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Best Answer
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MartinLiebig Administrator, Moderator, Employee-RapidMiner, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,533
RM Data Scientist
so a 2sigma effect. I would not worry.
- Sr. Director Data Solutions, Altair RapidMiner -
Dortmund, Germany5
Answers
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MartinLiebig Administrator, Moderator, Employee-RapidMiner, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,533
RM Data Scientist
Hi,I would use a cross validation to check for the std_dev of the performance. Then you can see how lucky you are.Best,Martin- Sr. Director Data Solutions, Altair RapidMiner -
Dortmund, Germany0 -
MartinLiebig Administrator, Moderator, Employee-RapidMiner, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,533
RM Data Scientist
I would do the same trick there
But generally, if testing is better than training its rather unproblematic- Sr. Director Data Solutions, Altair RapidMiner -
Dortmund, Germany1
Learner I