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Difference between normal decision tree with information gain criterion and W-J48
Contributor I
Hi. Have a good day everyone!
I want to ask a question
1st question
What is the difference between
a) normal decision tree with information gain criterion and
b) W-J48?
Im quite confused with the difference.
Why dont we just use the basic decision tree and choose 'Information gain' for the criterion instead of using W-J48?
2nd question
Is there any guidelines for me to set the suitable values for parameters in W-J48 such as the confidence threshold for pruning and the minimum number of instances per leaf?
I dont know the suitable value that should be set for the parameters.
I want to ask a question
1st question
What is the difference between
a) normal decision tree with information gain criterion and
b) W-J48?
Im quite confused with the difference.
Why dont we just use the basic decision tree and choose 'Information gain' for the criterion instead of using W-J48?
2nd question
Is there any guidelines for me to set the suitable values for parameters in W-J48 such as the confidence threshold for pruning and the minimum number of instances per leaf?
I dont know the suitable value that should be set for the parameters.
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Telcontar120
Moderator, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,635 
Unicorn
I think this is a similar discussion to the following thread: https://community.rapidminer.com/discussion/54804/difference-between-c4-5-and-w-j48#latest
For more details on the W-J48 implementation you should consult the Weka project documentation.
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