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"Decision Trees RM 4 vs RM 5"
Hi,
I have a model in RM 4.0 that uses decision trees. I have got the best result by setting no_pre_pruning to true (according to a 10 folds cross validation.)
However, implementing the same model in RM 5.0 shows that the accuracy is reduced by around 50%.
By setting no_pre_pruning to false provides similar results in both versions.
Am I missing anything?
Thanks in advanced
I have a model in RM 4.0 that uses decision trees. I have got the best result by setting no_pre_pruning to true (according to a 10 folds cross validation.)
However, implementing the same model in RM 5.0 shows that the accuracy is reduced by around 50%.
By setting no_pre_pruning to false provides similar results in both versions.
Am I missing anything?
Thanks in advanced
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Answers
umpf. I can't really say anything about this. Sorry. No idea at all. Did anybody make similar experiences?
Greetings,
Sebastian
do you have a sample data set and RapidMiner data mining process for us to reproduce the results?
Best regards,
Ralf
I have the required data how can I send it to you?
if neither the data nor the process are confidential, you could post the process here. Simply use the insert code button (#) in the forum editor to insert the XML source of the RapidMiner process. Regarding the data set: If it is small, you could also use insert to post it here. This way the community could benefit from the discussion of this issue
If the data set is large or confidential, you can send it to us via e-mail.
Best regards,
Ralf
Below is the code and data.
RM4 Code RM5Code and the data